{"id":"W4376612848","doi":"10.36850/mr6","title":"Reflections on Preregistration: Core Criteria, Badges, Complementary Workflows","year":2023,"lang":"en","type":"article","venue":"Journal of Trial and Error","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Canadian Institutes of Health Research; Arnold Ventures","keywords":"Leverage (statistics); Psychology; Workflow; Context (archaeology); Core (optical fiber); Social psychology; Applied psychology; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.03737625,0.0001206636,0.001329006,0.0003531271,0.000183772,0.0004247792,0.0004693792,0.00003950465,0.005631712],"category_scores_gemma":[0.006199567,0.00005572796,0.000793648,0.0008225879,0.00002888289,0.000179269,0.00003951741,0.0001410222,0.0004055992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001621041,"about_ca_system_score_gemma":0.00004738754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005779165,"about_ca_topic_score_gemma":0.00005033684,"domain_scores_codex":[0.9912599,0.001557268,0.004743932,0.0002415764,0.002076264,0.0001210358],"domain_scores_gemma":[0.9946339,0.001364341,0.002821123,0.0006140783,0.0004377668,0.0001288076],"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":[0.001602593,0.0000687442,0.0003937646,0.00001273081,0.0001815518,0.0000254484,0.0004369914,0.00008816768,0.0002019576,0.0009225126,0.9845056,0.01155993],"study_design_scores_gemma":[0.007825457,0.001270492,0.005681159,0.00009361327,0.0003078029,0.00009632614,0.002282221,0.001902715,0.0000126408,0.01686682,0.9635098,0.0001509319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9560573,0.0004802453,0.001788308,0.01939345,0.006125906,0.0009560619,0.00004504245,0.000009552722,0.01514416],"genre_scores_gemma":[0.9704065,0.0001303048,0.005297942,0.0008163707,0.002819825,0.00001454387,0.00001309577,0.00001196294,0.02048948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03117669,"threshold_uncertainty_score":0.9952773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9321029567355448,"score_gpt":0.6470500933930182,"score_spread":0.2850528633425266,"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."}}