{"id":"W6929658342","doi":"10.48660/23050098","title":"LECTURE: Generative Modelling","year":2023,"lang":"en","type":"other","venue":"PIRSA","topic":"Statistical Methods and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Generative grammar; Feature (linguistics); Generative model; Set (abstract data type); Representation (politics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008933352,0.0001368504,0.0002171728,0.00005479947,0.00003358016,0.00001541217,0.00009552095,0.0001417485,0.001287073],"category_scores_gemma":[0.000180299,0.000114058,0.0000485003,0.0001118836,0.00002668903,0.000004476204,0.00002467042,0.0001376344,0.0004653914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001787462,"about_ca_system_score_gemma":0.00001557932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006555997,"about_ca_topic_score_gemma":0.00009424109,"domain_scores_codex":[0.9993876,0.00003396006,0.0001222255,0.0002085007,0.0001124259,0.0001353228],"domain_scores_gemma":[0.9990682,0.0005447037,0.00007604068,0.000251642,0.00001508006,0.00004434429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[4.508662e-7,0.00001553369,3.371486e-7,0.00003458258,0.00003806235,0.000002207002,0.00004993795,0.00002620308,0.000006842685,0.4588901,0.5330771,0.00785868],"study_design_scores_gemma":[0.00004383863,0.00000481718,2.189902e-7,0.0000512661,0.00004153238,4.625579e-7,0.000004091621,0.005420686,0.00003736417,0.5997508,0.3945183,0.0001267336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[2.979418e-7,0.0001104216,0.6962685,0.00009459155,0.00009455309,0.000148055,0.00009076043,0.0004294484,0.3027633],"genre_scores_gemma":[0.000009254191,0.00007946232,0.6579342,0.00004719965,0.0004396935,0.00008346197,0.000006847413,0.0006371,0.3407628],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1408607,"threshold_uncertainty_score":0.9996259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1561536327913481,"score_gpt":0.400334504198175,"score_spread":0.2441808714068269,"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."}}