{"id":"W7094443519","doi":"","title":"Generative AI & Competition Law Concerns: The New Kid on the Block!","year":2024,"lang":"en","type":"article","venue":"Goldsmiths (University of London)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Generative grammar; Parliament; Applications of artificial intelligence; Set (abstract data type); Human intelligence; Artificial general intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003413945,0.0001113633,0.0002184914,0.00008278676,0.0003805378,0.00009717749,0.0003618439,0.00004731942,0.005917518],"category_scores_gemma":[0.00001597509,0.00009273216,0.0001609113,0.0002007269,0.0004051106,0.0002197466,0.0001273412,0.0001506224,0.01097792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008924934,"about_ca_system_score_gemma":0.00003155382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254588,"about_ca_topic_score_gemma":0.0005589073,"domain_scores_codex":[0.9992825,0.00002015174,0.0001530922,0.0003257566,0.00004531079,0.0001731927],"domain_scores_gemma":[0.9993789,0.0001329469,0.0001105943,0.0003045716,0.00002570716,0.00004724486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009750469,0.0000116688,0.0000747122,0.000006147551,0.00009086924,0.000002479828,0.001947443,0.00008975989,0.000003854052,0.6628292,0.3347532,0.0001809181],"study_design_scores_gemma":[0.0002528583,0.00002948476,0.0003038814,0.00002897836,0.00001820679,0.000001665159,0.001901444,0.0011199,0.00002547658,0.01527668,0.9809152,0.0001261551],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05649215,0.002874909,0.002873587,0.05971571,0.003450608,0.0005007347,0.001038587,0.0001217581,0.872932],"genre_scores_gemma":[0.7317641,0.000473356,0.0001981005,0.001914131,0.0001877115,8.246406e-7,0.00001115029,0.00001209582,0.2654385],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.675272,"threshold_uncertainty_score":0.9949912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04137697474686178,"score_gpt":0.2036128457631655,"score_spread":0.1622358710163038,"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."}}