{"id":"W6938827644","doi":"10.6068/dp15d41df095276","title":"TREND: Xignite. FactSet Corporate Fundamentals: Number of Employees | Stock Symbol: AAPL | Symbol Name: Apple Inc, 09/30/2011 - 09/30/2016. 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":"Stock (firearms); Earnings; CONQUEST; Stock market; Context (archaeology); Stock exchange","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":[],"consensus_categories":[],"category_scores_codex":[0.0009630646,0.002125832,0.001448011,0.005018944,0.0008050435,0.003381822,0.002817906,0.002231312,0.1111239],"category_scores_gemma":[0.005931024,0.0007682081,0.001026214,0.009568437,0.0003249962,0.00253451,0.001866065,0.002102014,0.2219719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001730527,"about_ca_system_score_gemma":0.002468941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03999404,"about_ca_topic_score_gemma":0.05576318,"domain_scores_codex":[0.9991369,0.0000826411,0.00008071733,0.000296532,0.0002512531,0.0001519856],"domain_scores_gemma":[0.9973266,0.0004265464,0.0003209421,0.0005849545,0.001078841,0.0002621958],"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":[0.0000172774,0.000008422731,0.0005939761,0.0001236137,0.000009496938,0.000008687148,0.00000781021,0.0001075113,0.00003215866,0.000253472,0.9976898,0.001147718],"study_design_scores_gemma":[0.0001318841,0.00002085593,0.004598683,0.000257361,0.00002115519,0.00004076836,0.00007470292,0.0006116995,0.0002445631,0.0008980779,0.9930717,0.00002847122],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008742719,0.0000301865,0.00003380502,0.00006716701,0.00002302355,0.000008501414,0.9985397,0.0003411707,0.0008691004],"genre_scores_gemma":[0.0001749986,0.00002917867,0.0001055365,0.00003964277,0.000008883931,0.00003459565,0.9986993,0.00005612178,0.0008517816],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1111239,"threshold_uncertainty_score":0.3717464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05743661650791723,"score_gpt":0.3149142559224645,"score_spread":0.2574776394145473,"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."}}