{"id":"W4405353140","doi":"10.31234/osf.io/r5n6f","title":"Throwing good effort after bad: Evidence for a sunk-cost effect in cognitive effort-based decision-making","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Sunk costs; Throwing; Cognition; Cognitive psychology; Psychology; Economics; Microeconomics; Computer science; Social psychology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004508825,0.000438264,0.0006372559,0.0004287631,0.0003230932,0.001245253,0.0004185874,0.0008240164,0.005912627],"category_scores_gemma":[0.02463312,0.0003973275,0.0004892006,0.0002931785,0.001238126,0.0009140561,0.00121456,0.001297276,0.0003090061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002690748,"about_ca_system_score_gemma":0.0002420401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029774,"about_ca_topic_score_gemma":0.001243504,"domain_scores_codex":[0.9982948,0.0006411831,0.0001064048,0.0004809559,0.0003329721,0.0001437658],"domain_scores_gemma":[0.9708354,0.01939241,0.004203183,0.003696859,0.0006519303,0.001220273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02396107,0.005696183,0.7051226,0.001893271,0.002886863,0.0008057196,0.005205176,0.003978234,0.09136751,0.008648995,0.001113925,0.1493204],"study_design_scores_gemma":[0.0001643658,0.0009285351,0.9873127,0.00005531317,0.0002813356,0.0001626892,0.0002408134,0.001733885,0.003329263,0.00505982,0.0006904934,0.00004066866],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935628,0.000407415,0.001997646,0.000175613,0.00002989208,0.00001589685,0.00008322056,0.00001517491,0.003712348],"genre_scores_gemma":[0.9982059,0.0001324026,0.001016215,0.0001296516,0.00001997169,0.00001593671,0.00005777843,0.00001920091,0.0004027491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005912627,"threshold_uncertainty_score":0.0238452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1657979132891187,"score_gpt":0.479482525023664,"score_spread":0.3136846117345453,"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."}}