{"id":"W6960694273","doi":"10.1371/journal.pone.0087910.t001","title":"Demographics and baseline characteristics: ITT population.","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demographics; WOMAC; Body mass index; Baseline (sea); Osteoarthritis; Body weight","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002768299,0.0001610221,0.0002711246,0.0001359915,0.0003716787,0.000168094,0.0002658326,0.0003962199,0.08372389],"category_scores_gemma":[0.002196294,0.0001407648,0.00009106581,0.0003004999,0.00003246704,0.0001479969,0.00009909393,0.0002467735,0.0007988717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004111855,"about_ca_system_score_gemma":0.0001712657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007554155,"about_ca_topic_score_gemma":0.002816783,"domain_scores_codex":[0.9987139,0.0001813075,0.0002047129,0.0002594419,0.0004349805,0.0002056302],"domain_scores_gemma":[0.9989706,0.0001034774,0.0001983597,0.0002381479,0.0002568843,0.0002325905],"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":[0.000001779097,0.00001217344,0.00008365052,0.00008720988,0.0000270902,0.00001044132,0.00005175385,2.133959e-7,1.869787e-8,0.000005660995,0.999188,0.0005319777],"study_design_scores_gemma":[0.00004807703,0.000006555318,0.00094473,0.0003311784,0.0000714009,7.479259e-7,0.00003323831,0.000007345356,4.629201e-8,0.00004434795,0.9983148,0.0001975535],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009308033,0.0005025364,3.366792e-8,0.0001722146,0.0001171981,0.0001121345,0.9988889,0.00003573929,0.0001619504],"genre_scores_gemma":[0.0001414405,0.00008780885,0.000006473301,0.0002040315,0.00118454,0.00002504983,0.9976074,0.000008379495,0.0007349269],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08292501,"threshold_uncertainty_score":0.9999791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04096478140490512,"score_gpt":0.3084483300064009,"score_spread":0.2674835486014958,"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."}}