{"id":"W6906409077","doi":"10.17605/osf.io/fuz8t","title":"Figures","year":2018,"lang":"en","type":"article","venue":"Open Science Framework","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Process (computing); Identification (biology); Work (physics); Product (mathematics)","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":[0.001012146,0.001792735,0.0009149348,0.00474237,0.001655482,0.004861296,0.002244313,0.002587886,0.9026477],"category_scores_gemma":[0.01112834,0.0005386329,0.001530171,0.003437378,0.0007257474,0.003311928,0.002046996,0.002241079,0.7641896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042944,"about_ca_system_score_gemma":0.003137794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017401,"about_ca_topic_score_gemma":0.01001975,"domain_scores_codex":[0.9989898,0.0001072539,0.00004655401,0.0002162186,0.0005233006,0.0001168922],"domain_scores_gemma":[0.9967525,0.0008290536,0.000184321,0.0006800019,0.001220418,0.0003337971],"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":[0.00003520401,0.00002162753,0.0001343006,0.0001566257,0.000008723547,0.00003185295,0.00002474699,0.0002975687,0.0001372258,0.008792106,0.9752091,0.01515099],"study_design_scores_gemma":[0.0000332933,0.000005120229,0.0002953512,0.0001352009,0.000009162977,0.00004029546,0.00005017559,0.0002009479,0.0002002542,0.00723656,0.9917815,0.00001212456],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.0007926904,0.0007050149,0.009271693,0.003169211,0.009275041,0.000380656,0.3307199,0.009228855,0.6364568],"genre_scores_gemma":[0.01018604,0.001723324,0.01891081,0.002110749,0.001563455,0.0009938012,0.405197,0.008571838,0.550743],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.09735233,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04643158541042548,"score_gpt":0.4013942361261712,"score_spread":0.3549626507157457,"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."}}