{"id":"W4414833938","doi":"10.29173/alr2848","title":"Vavilov and Generative AI","year":2025,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Generative grammar; Set (abstract data type); Citizenship; Basis (linear algebra); Generative model","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032515,0.0001744739,0.0003798198,0.00002788915,0.0001245485,0.0001274471,0.0006499962,0.00004258989,0.00003579447],"category_scores_gemma":[0.0001299104,0.0001409806,0.00008381314,0.0004729113,0.00009122732,0.0002814134,0.0006120657,0.0001334212,0.00007763477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003297064,"about_ca_system_score_gemma":0.00006483573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000597422,"about_ca_topic_score_gemma":0.0006365236,"domain_scores_codex":[0.9986631,0.0001755882,0.0002665025,0.0005364195,0.0001353923,0.0002230302],"domain_scores_gemma":[0.9985855,0.0003879961,0.00005612208,0.0007958516,0.00009561371,0.00007897126],"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":[3.427348e-7,0.00003160633,0.0001259597,0.0004400608,0.00001954168,0.000003000919,0.00004350081,0.000001882083,0.000006949408,0.8908316,0.006627194,0.1018683],"study_design_scores_gemma":[0.0001498931,0.00004239438,0.0003217502,0.000928381,0.00002799594,0.00001967602,6.166777e-7,0.005907671,0.0001126164,0.02444158,0.9678259,0.0002214473],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.0004704349,0.3539696,0.3681334,0.1588659,0.001385055,0.001931444,0.00000277342,0.0002410991,0.1150002],"genre_scores_gemma":[0.1033172,0.1340201,0.2348517,0.5092658,0.0005045524,0.0005999136,0.00002719818,0.0000699751,0.01734354],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9611988,"threshold_uncertainty_score":0.5749021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01199585371072098,"score_gpt":0.2856844672051997,"score_spread":0.2736886134944787,"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."}}