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Ground-level proof points accumulating

Ground-level proof points accumulating: management narrates several small, named, recent wins and treats them as the lea

Calls Tested
322
Answered YES
8
Hit Rate
2.5%
rare by design

Leggett & Platt, Incorporated (LEG) — this company's answers

NO on the Q3 2021 call 2021-11-02 C
The model's full reasoning — Q3 2021 call → NO我们根据提供的电话会议记录,判断管理层的叙述是否包含多个具体、可识别的近期事件,并且管理层是否将这些事件联系起来,视为一个仍在早期阶段的更广泛改善趋势。 首先,寻找具体事件。记录中提到了: - 欧洲Bedding业务在第三季度软化,但Kayfoam收购于6月完成,带来长期增长机会。 - 汽车业务受半导体短缺影响,产量下降。 - 航空航天业务中,导管组件需求接近2019年水平,但焊接和无缝管产品仍低于疫情前。 - 液压缸需求强劲,订单积压增长。 - 家居家具业务需求强劲。 - 工作家具连续第五个季度环比改善。 - 地理组件业务销量下降。 - 织物转换业务因医疗和过滤销售激增不再重现而下降。 - 地板业务受化学供应、劳动力和运输影响。 这些大多是业务趋势和宏观因素,而非具体、可识别的近期事件。例如,Kayfoam收购是6月完成的,但记录中未描述具体事件如新客户、新工厂等。工作家具的连续改善是趋势,不是单个事件。没有提到具体客户签约、新工厂开业、产品首发等。 因此,缺乏至少三个独立、具体、可识别的近期事件。管理层的叙述主要是总体业绩和行业挑战,而非具体操作层面的胜利。 其次,管理层是否将这些事件连接为早期阶段的更广泛改善?记录中,管理层提到“我们继续应对各种宏观市场挑战”,并强调“我们仍然处于有利地位”,但未明确将具体事件连接为正在形成的、仍处于早期阶段的模式。例如,关于汽车,管理层说“一旦供应链稳定,行业应该看到生产改善”,但这是展望,不是基于具体事件的模式。 因此,答案应为NO。

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Show the exact prompt the model was given
Using ONLY the supplied earnings call transcript and no outside information: On this call, does management's account of the just-reported period rest on SEVERAL SMALL, CONCRETE, GROUND-LEVEL WINS THAT IT NAMES AND DESCRIBES INDIVIDUALLY — specific recent episodes from inside the business, each one identifiable on its own — AND does management explicitly treat these accumulating episodes as the LEADING EDGE of a broader improvement that is still early? Answer YES when BOTH halves come through in management's own words, in whatever form fits the business: (1) AT LEAST THREE DISTINCT, NAMED OR INDIVIDUALLY IDENTIFIABLE EPISODES FROM THE RECENT PERIOD. Management recounts multiple separate ground-level events that actually happened recently — each described specifically enough that a listener could tell the episodes apart and could later check them. The episodes may take whatever form fits the industry: a particular customer, account, or partner that signed, reordered, expanded, or went live; a particular site, store, plant, line, rig, clinic, or facility that opened, hit a milestone, or reached a new performance level; a particular product, program, or offering that shipped its first units, won its first placements, or crossed a threshold; a particular region, channel, or contract that turned on or stepped up. What matters is the GRANULARITY and RECENCY: these are individually small, freshly occurred, operator-level facts — the kind of detail only people close to the business would narrate — not aggregate results, percentages, themes, or claims like "demand was strong across the board." (2) MANAGEMENT ITSELF CONNECTS THE EPISODES INTO A BUILDING PATTERN THAT IS STILL EARLY. Management explicitly draws the line from these individual episodes to a larger developing trajectory — conveying, in its own voice, that these wins are instances of the same underlying thing, that more of the same kind are already forming or arriving, and that the pattern's contribution to reported results is only beginning, so most of it lies ahead. The generalization must be management's own act, grounded in the recounted episodes — not a hope, a market-size claim, or an analyst's summary. Answer NO if the call's positive story is carried mainly by aggregates — overall growth rates, segment percentages, or general demand commentary — without several individually identifiable recent episodes. NO if fewer than three distinct episodes are described, or the episodes are really one event told from different angles. NO if the episodes are plans, pipeline items, letters of intent, or hoped-for events rather than things that already happened. NO if the episodes are the routine cadence this company always reports (its usual pace of customer additions, standard seasonal openings) and management does not present their accumulation as new or building. NO if management recounts the episodes but never itself connects them into a broader, still-early pattern with more arriving. NO if the episodes chiefly explain problems, or the call is mainly defense of weak results. NO if the pattern-framing appears only in an analyst's question or summary that management does not itself adopt. Use only the supplied transcript. Answer only YES or NO.

Companies that answered YES

TickerCompanyCallDateCall grade
CRGO Freightos Limited Q1 2024 2024-05-20 C+
MBLY Mobileye Global Inc. Q2 2023 2023-07-28 B+
TOST Toast, Inc. Q4 2022 2023-02-16 C+
BXP Boston Properties, Inc. Q1 2022 2022-05-03 A
AU AngloGold Ashanti's Q2 2018 2018-08-20 B
MITK Mitek Systems, Inc. Q4 2017 2017-11-07 C+
TGI Triumph Group, Inc. Q2 2017 2016-11-03 C+
GOGO Gogo Inc. Q1 2016 2016-05-06 C+

How the model reasoned

AU · Q2 2018 → YESThe question is: Does management's account of the just-reported period rest on SEVERAL SMALL, CONCRETE, GROUND-LEVEL WINS THAT IT NAMES AND DESCRIBES INDIVIDUALLY — specific recent episodes from insid...YES The transcript shows multiple specific, recent operational episodes: Kibali’s underground ramp-up with automated ore handling system and vertical shaft integration; Iduapriem’s CIL tank conversion and grade/tonnage gains; Sunrise Dam’s Recovery Enhancement Project plus new mining strategies; Tropicana’s second 6-MW ball mill installation; Siguiri’s CIL circuit milestone; and 338 tracked Operational Excellence projects.
BXP · Q1 2022 → YESThe question is: Does management's account of the just-reported period rest on SEVERAL SMALL, CONCRETE, GROUND-LEVEL WINS THAT IT NAMES AND DESCRIBES INDIVIDUALLY — specific recent episodes from insid...YES The transcript shows multiple distinct, named episodes from the recent period: the 73,000 sq ft recapture/release at 77 CityPoint with a 15% rent increase and 7.
CRGO · Q1 2024 → YESThe question is: Does management's account of the just-reported period rest on SEVERAL SMALL, CONCRETE, GROUND-LEVEL WINS THAT IT NAMES AND DESCRIBES INDIVIDUALLY — specific recent episodes from insid...

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Not investment advice. Artul.ai publishes AI-generated earnings-call quality grades and expected-volatility estimates — never buy or sell recommendations. We tested over 1,600 predictive hypotheses against 165,000 transcripts; the honest result, including what failed, is documented in our methodology.