{"id":"W4313476081","doi":"10.1287/mnsc.2022.4496","title":"Experimental Choice and Disruptive Technologies","year":2023,"lang":"en","type":"article","venue":"Management Science","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Anticipation (artificial intelligence); Competition (biology); Context (archaeology); Economics; Microeconomics; Industrial organization; Balance (ability); False positive paradox; Marketing; Business; Computer science; Psychology","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":[0.04433474,0.0006261485,0.0007026296,0.0007312281,0.0009279661,0.003288164,0.001414322,0.002699735,0.004210115],"category_scores_gemma":[0.1317579,0.0004388549,0.0006700347,0.0007993818,0.008513419,0.003796433,0.002213977,0.002532019,0.0003596692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002118923,"about_ca_system_score_gemma":0.001057338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003324958,"about_ca_topic_score_gemma":0.000318455,"domain_scores_codex":[0.9567262,0.03261541,0.001228793,0.003043238,0.00537668,0.001009692],"domain_scores_gemma":[0.7220783,0.2311957,0.02575891,0.01632996,0.002991467,0.001645748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004779733,0.001287276,0.04395494,0.0008190244,0.000585073,0.000419555,0.001857542,0.02070473,0.01521988,0.8284288,0.001558052,0.08038542],"study_design_scores_gemma":[0.0008473502,0.004056885,0.02346491,0.0002629576,0.0002866249,0.0005510136,0.0008420352,0.02582239,0.01572908,0.9124091,0.01550225,0.000225283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6902017,0.004197758,0.2114169,0.0118254,0.0005219463,0.0007660431,0.0002913088,0.0002045946,0.08057424],"genre_scores_gemma":[0.9771403,0.0006631018,0.01777888,0.001205909,0.0001306972,0.0005340061,0.00004603493,0.00002441544,0.002476731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04433474,"threshold_uncertainty_score":0.2344673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02418047599499843,"score_gpt":0.2769702994485804,"score_spread":0.252789823453582,"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."}}