{"id":"W6938942430","doi":"10.6068/dp15c1c1160731","title":"Trend. Xignite. FactSet Corporate Fundamentals: 3-Year Annual Revenue Growth Rate | Country: USA | 318_0_0: FBLQ | 318_0_3: Football Equities Inc | 318_0_1: Other OTC/NBB, Day Format Error: 2147483647-Day Format Error: 0. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 016-005-006.","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 exchange; Earnings; Annual report; Revenue; Stock (firearms); Stock market; Annual growth %; Growth stock","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":[0.001181105,0.002169996,0.001407969,0.004249679,0.0008825025,0.003766743,0.003335089,0.002406456,0.1724695],"category_scores_gemma":[0.007053445,0.0009836958,0.001477794,0.008478975,0.0003477838,0.003051245,0.002378776,0.002684845,0.3196606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00169629,"about_ca_system_score_gemma":0.001962028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.027664,"about_ca_topic_score_gemma":0.0341549,"domain_scores_codex":[0.9989432,0.0001139246,0.000113345,0.0003618648,0.0002773778,0.0001903924],"domain_scores_gemma":[0.9967819,0.000646124,0.0003623534,0.0007523777,0.001186632,0.0002706667],"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":[0.00001583358,0.000007826471,0.0005096672,0.0001330168,0.000008954628,0.000007085018,0.000008949276,0.00009192199,0.0000287798,0.0002083516,0.9979486,0.001031116],"study_design_scores_gemma":[0.0001626103,0.00002308994,0.004280142,0.0003069764,0.00001844261,0.00003278252,0.00008732914,0.0004830891,0.0002789348,0.0008835564,0.9934117,0.0000313691],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005152878,0.00001524807,0.00002750415,0.00005299839,0.0000248742,0.000007030174,0.9989175,0.0003472592,0.0005561979],"genre_scores_gemma":[0.0001424102,0.00002092202,0.000123271,0.00003487258,0.000009067805,0.00004539267,0.9987557,0.00009685607,0.0007716166],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1724695,"threshold_uncertainty_score":0.5769679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08345435887831501,"score_gpt":0.3126177478052187,"score_spread":0.2291633889269037,"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."}}