{"id":"W6920586152","doi":"10.6068/dp15d41edcc6d86","title":"TREND: Xignite. FactSet Corporate Fundamentals: Number of Employees | Stock Symbol: IBM | Symbol Name: International Business Machines Corp, 12/31/2011 - 12/31/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 016-005-118","year":2017,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"IBM; Earnings; Stock (firearms); CONQUEST; Stock market; International market; Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009995893,0.002285954,0.001498026,0.005226813,0.000857205,0.003202789,0.002991692,0.002341723,0.09694093],"category_scores_gemma":[0.005823012,0.0007465154,0.001137215,0.009570222,0.0003379683,0.002483826,0.001842524,0.002159314,0.2061075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00173811,"about_ca_system_score_gemma":0.00253112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04033164,"about_ca_topic_score_gemma":0.05714222,"domain_scores_codex":[0.9991044,0.00009193336,0.00008350639,0.0003067211,0.0002526335,0.0001607886],"domain_scores_gemma":[0.997498,0.0004100942,0.0002901596,0.0005574462,0.0009931228,0.0002512367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001886725,0.000009217991,0.0005943319,0.0001361968,0.00001041674,0.000009301938,0.000008239944,0.0001200042,0.00003486898,0.000251331,0.9976447,0.001162653],"study_design_scores_gemma":[0.0001493353,0.00002307395,0.004668477,0.000268597,0.00002434683,0.00004634838,0.00008229267,0.0007390398,0.0002550659,0.001027285,0.9926847,0.00003139724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009622506,0.00003263917,0.00003759763,0.00006957693,0.00002406788,0.000009209752,0.9985598,0.0003825246,0.0007882795],"genre_scores_gemma":[0.0001679272,0.00002742945,0.0001164673,0.0000378365,0.00000820592,0.00003422412,0.9988492,0.00005272547,0.0007060765],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9030591,"threshold_uncertainty_score":0.3242998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.057252979662596,"score_gpt":0.3176581628974591,"score_spread":0.2604051832348631,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}