{"id":"W7052835055","doi":"","title":"TUT0601 Group 2: Replication of Diener, E., Ng, W., Harter, J., & Arora, R. (2010). - University of Toronto W19","year":2019,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Electrostatic Discharge in Electronics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Replication (statistics); Diener; Group (periodic table); Statistician","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04707099,0.001837942,0.001761291,0.004505274,0.00593657,0.005586446,0.003637167,0.003010415,0.107501],"category_scores_gemma":[0.1691983,0.001440148,0.002352767,0.006377089,0.002281722,0.002527976,0.007352986,0.003553867,0.05884925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003522054,"about_ca_system_score_gemma":0.01296611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02585559,"about_ca_topic_score_gemma":0.03932435,"domain_scores_codex":[0.9641249,0.01616241,0.0031183,0.003307851,0.011146,0.00214042],"domain_scores_gemma":[0.8007913,0.01561073,0.005179219,0.09642068,0.07530217,0.00669592],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005195025,0.0007763472,0.01142346,0.0009257945,0.0003937427,0.0002573819,0.003085445,0.0007161809,0.006363235,0.01673193,0.8898022,0.06432917],"study_design_scores_gemma":[0.001615146,0.001433486,0.04330549,0.0005322371,0.0003483368,0.0003039317,0.001523704,0.001018856,0.00496533,0.008915057,0.9357681,0.0002703466],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.09778222,0.001686617,0.1085202,0.01305389,0.04768625,0.05339767,0.4697055,0.01160433,0.1965634],"genre_scores_gemma":[0.1698513,0.0006516406,0.1183009,0.01127012,0.003594083,0.1289777,0.3162142,0.01820467,0.2329355],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.952929,"threshold_uncertainty_score":0.3596266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010471366509449,"score_gpt":0.2220669055855267,"score_spread":0.2115955390760778,"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."}}