{"id":"W4404620139","doi":"10.1111/deci.12658","title":"Explanation seeking and anomalous recommendation adherence in human‐to‐human versus human‐to‐artificial intelligence interactions","year":2024,"lang":"en","type":"article","venue":"Decision Sciences","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Queen's University","funders":"","keywords":"Loss aversion; Set (abstract data type); Sunk costs; Preference; Computer science; Recommender system; Risk aversion (psychology); Bayesian inference; Human intelligence; Psychology; Artificial intelligence; Bayesian probability; Machine learning; Microeconomics; Economics; Expected utility hypothesis","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":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006472208,0.0002659062,0.0003767208,0.002760384,0.001081668,0.003299576,0.001221555,0.0001042311,0.001124957],"category_scores_gemma":[0.002530959,0.000220195,0.0001022271,0.003671364,0.0002298405,0.001642935,0.0004983136,0.0003104912,0.001099689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002163074,"about_ca_system_score_gemma":0.00009576217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002870056,"about_ca_topic_score_gemma":0.003540468,"domain_scores_codex":[0.9950826,0.0001584239,0.001546199,0.001527701,0.001243061,0.0004420427],"domain_scores_gemma":[0.9953194,0.003456863,0.0002167769,0.0004874812,0.0002490885,0.0002704058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004427393,0.00006227806,0.00101799,0.000001596366,0.000002530721,0.00001799149,0.001365235,0.0005731612,0.004324259,0.008265671,0.001635931,0.9826891],"study_design_scores_gemma":[0.0004115217,0.002378366,0.01808347,0.0008831272,0.00003148651,0.00006657654,0.01360932,0.03929663,0.003142805,0.8792916,0.04141913,0.001385972],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9502547,0.00003723985,0.04247229,0.001100899,0.002855089,0.0003333047,0.00002388301,0.00009030375,0.002832248],"genre_scores_gemma":[0.9943012,0.000005923691,0.005167048,0.000164962,0.0001523531,0.00003798856,0.000008816449,0.00001514222,0.0001465945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9813031,"threshold_uncertainty_score":0.9997882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4282554302534988,"score_gpt":0.5369649849622157,"score_spread":0.1087095547087169,"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."}}