{"id":"W2760681975","doi":"10.12688/f1000research.12715.1","title":"Make researchers revisit past publications to improve reproducibility","year":2017,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Open peer review; Scientific publishing; Publishing; Plant biology; Computer science; Data science; Engineering ethics; Medicine; Political science; Engineering; Biology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","open_science","insufficient_payload"],"category_scores_codex":[0.6611049,0.0007000071,0.00556263,0.002283653,0.001047553,0.01548,0.02490233,0.0005480585,0.04582826],"category_scores_gemma":[0.6890298,0.0003977065,0.003397464,0.002686984,0.0004878755,0.0003325841,0.01522131,0.002774224,0.06738685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004324969,"about_ca_system_score_gemma":0.001582161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004087677,"about_ca_topic_score_gemma":0.0002435973,"domain_scores_codex":[0.8531972,0.0596385,0.02153062,0.01889047,0.0443446,0.002398628],"domain_scores_gemma":[0.7707287,0.01490078,0.009152456,0.1762994,0.02616308,0.002755614],"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":[0.00002325486,0.0001157176,0.02113017,0.0003178783,0.0002702478,0.000009197287,0.0003831927,0.000051586,0.0001859104,0.001287008,0.8215454,0.1546805],"study_design_scores_gemma":[0.0001077389,0.00004647835,0.05888486,0.0001733431,0.00008377532,0.00000347389,0.0002154713,0.001362191,0.00007473474,0.03198945,0.9066525,0.0004060284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06505071,0.005136432,0.01747907,0.3086016,0.00317295,0.02936418,0.0018239,0.0001546675,0.5692165],"genre_scores_gemma":[0.134757,0.0002430566,0.01114398,0.0004108453,0.001837141,0.002538446,0.0001882291,0.0001070147,0.8487743],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3081908,"threshold_uncertainty_score":0.9998475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9290358731683478,"score_gpt":0.6633959446979258,"score_spread":0.2656399284704219,"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."}}