{"id":"W4242753874","doi":"10.31234/osf.io/hvfmr","title":"Preregistration of secondary data analysis: A template and tutorial","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Popularity; Computer science; Data science; Selection (genetic algorithm); Psychology; Artificial intelligence; Social psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.001363426,0.00009622907,0.0003749397,0.0001647236,0.0001094709,0.0001973639,0.0007335143,0.00011617,0.0004326948],"category_scores_gemma":[0.0001457265,0.00008629957,0.00009776987,0.0002164671,0.0001316427,0.000273343,0.001213928,0.0001929127,0.000005291476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001187283,"about_ca_system_score_gemma":0.0004280348,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01388093,"about_ca_topic_score_gemma":0.0231841,"domain_scores_codex":[0.9985644,0.0001747094,0.000306907,0.0005107516,0.0003189244,0.0001243093],"domain_scores_gemma":[0.9984,0.0001123383,0.0002925829,0.001094235,0.00004655647,0.00005425742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002331037,0.0007410516,0.2910028,0.00262174,0.03538285,0.00002105057,0.07275489,0.005419886,0.0009886136,0.2086403,0.1223886,0.2598052],"study_design_scores_gemma":[0.001609234,0.0001384856,0.1379223,0.0006399112,0.02383513,0.000001099532,0.01980437,0.111306,0.0001632157,0.03463018,0.6671034,0.002846735],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3601071,0.001126998,0.0445583,0.001645437,0.002612846,0.001376727,0.007399415,0.0001661045,0.5810071],"genre_scores_gemma":[0.9924093,0.0003562637,0.001948001,0.00001664512,0.0004095052,0.000002452184,0.002603997,0.000004606519,0.002249238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6323022,"threshold_uncertainty_score":0.9946402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07596075832715285,"score_gpt":0.3757982647036783,"score_spread":0.2998375063765254,"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."}}