{"id":"W4413923498","doi":"10.1016/j.artint.2025.104408","title":"Incentives for responsiveness, instrumental control and impact","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Open Philanthropy Project","keywords":"Incentive; Instrumental variable; Control (management); Computer science; Business; Econometrics; Economics; Artificial intelligence; Microeconomics; Machine learning","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":[0.02434058,0.001176846,0.001865088,0.001708023,0.001530577,0.006233453,0.001851001,0.006134789,0.02365198],"category_scores_gemma":[0.102693,0.0007240425,0.0009464794,0.001487908,0.006812754,0.007348366,0.003661681,0.005516845,0.001110642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003257877,"about_ca_system_score_gemma":0.002624851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001470555,"about_ca_topic_score_gemma":0.001675893,"domain_scores_codex":[0.9846491,0.01012192,0.0004793483,0.001294619,0.001702728,0.00175222],"domain_scores_gemma":[0.8720639,0.1064015,0.008752741,0.006792747,0.002691692,0.003297309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001713938,0.0001514256,0.00227623,0.00009950227,0.0000595687,0.00008582394,0.0002369196,0.01206337,0.0003483612,0.9708523,0.001897409,0.01175772],"study_design_scores_gemma":[0.00009369697,0.00005747394,0.001682734,0.00003297921,0.00003090673,0.00005187155,0.0001833319,0.01466577,0.0001898925,0.9801584,0.002828945,0.00002408406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2146717,0.002379059,0.4533036,0.02958566,0.0004982068,0.0004736606,0.0006332518,0.000541064,0.2979139],"genre_scores_gemma":[0.9822955,0.0003289582,0.007353976,0.0007098744,0.0001775799,0.0001676598,0.00003474469,0.000041073,0.008890725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02434058,"threshold_uncertainty_score":0.1287268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03386361560293745,"score_gpt":0.3361751516129222,"score_spread":0.3023115360099847,"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."}}