{"id":"W6921023794","doi":"10.6084/m9.figshare.14926918.v1","title":"Additional file 1 of Comparing regression modeling strategies for predicting hometime","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre; University of Calgary","funders":"","keywords":"Calibration; Data set; Set (abstract data type); Regression analysis; Regression; Test set; Linear regression; Statistical model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005767441,0.001647724,0.001329143,0.001923956,0.0006743923,0.001376068,0.002339299,0.001553154,0.8443014],"category_scores_gemma":[0.1069668,0.0007942205,0.001734896,0.00282537,0.0002686436,0.001612932,0.0009891748,0.001666544,0.1302641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009362279,"about_ca_system_score_gemma":0.00194599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008029104,"about_ca_topic_score_gemma":0.01228026,"domain_scores_codex":[0.9982272,0.0008020271,0.0002107832,0.0003506751,0.0002752069,0.0001341817],"domain_scores_gemma":[0.8630662,0.1280401,0.00179099,0.00290652,0.003739873,0.0004562592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009446999,0.0002118632,0.003360931,0.003196629,0.0002105152,0.00006399066,0.00008792333,0.002744796,0.00007456564,0.001911331,0.9650784,0.02211442],"study_design_scores_gemma":[0.02040981,0.001438412,0.04438512,0.006595543,0.001435988,0.0008244709,0.0009503109,0.03585712,0.001631015,0.04546052,0.840632,0.0003797053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007879506,0.00006383988,0.003433693,0.0002649008,0.00006637373,0.0002967473,0.9923009,0.0009025334,0.001883182],"genre_scores_gemma":[0.04686997,0.0004967688,0.0449821,0.001596877,0.0003021767,0.01224008,0.8669077,0.005571153,0.02103321],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8443014,"threshold_uncertainty_score":0.2220852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.322687178963119,"score_gpt":0.407488843836682,"score_spread":0.08480166487356294,"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."}}