{"id":"W4414341611","doi":"10.1037/met0000770","title":"Crowdsourcing multiverse analyses to explore the impact of different data-processing and analysis decisions: A tutorial.","year":2025,"lang":"en","type":"article","venue":"Psychological Methods","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Crowdsourcing; Generalizability theory; Objectivity (philosophy); Focus (optics); Outcome (game theory); Heuristics; Conflation","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"],"consensus_categories":[],"category_scores_codex":[0.005737328,0.0001608864,0.0005619767,0.0005193589,0.0002609141,0.0002028183,0.00153994,0.0000937621,0.00009795275],"category_scores_gemma":[0.01620593,0.00006977274,0.0002648338,0.004422063,0.00019993,0.0001031907,0.0008078699,0.0001849687,0.000003389852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003027984,"about_ca_system_score_gemma":0.00001781466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007288376,"about_ca_topic_score_gemma":0.000004379363,"domain_scores_codex":[0.9970506,0.0009090841,0.0006937812,0.0007588523,0.0003945893,0.000193061],"domain_scores_gemma":[0.9898159,0.007911038,0.0002749846,0.001623001,0.0002573457,0.0001177414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00007359549,0.0001627907,0.006274627,0.000001015358,0.0001470875,7.254586e-7,0.000382577,0.0004211592,0.006271592,0.0003104224,0.00239477,0.9835596],"study_design_scores_gemma":[0.0004555616,0.0003925321,0.6883534,0.00008755478,0.0008392374,0.000004527291,0.002575219,0.1327055,0.001648798,0.1672035,0.005395067,0.000339056],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.301085,0.0001618031,0.6971952,0.0004276984,0.00005050898,0.0001722134,0.00002369644,0.00003697358,0.000846942],"genre_scores_gemma":[0.6115011,0.0000221989,0.3882995,0.00008135544,0.0000224359,0.0000266125,0.000003621366,0.000002754248,0.00004039245],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9832206,"threshold_uncertainty_score":0.992081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.757406363254655,"score_gpt":0.6943019283092987,"score_spread":0.06310443494535634,"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."}}