{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001044586,0.002198512,0.00189025,0.001969218,0.001333032,0.005593146,0.001310371,0.002059811,0.4723748],"category_scores_gemma":[0.003854408,0.0006583275,0.001523303,0.003078715,0.0008657413,0.003616032,0.002992085,0.003712494,0.3173497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002066366,"about_ca_system_score_gemma":0.001427443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002502683,"about_ca_topic_score_gemma":0.006474873,"domain_scores_codex":[0.9993157,0.0001413426,0.00002695144,0.0002087776,0.0002468631,0.00006042617],"domain_scores_gemma":[0.9987234,0.0005679163,0.00003636207,0.0002040602,0.0002119407,0.0002563257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004900132,0.00006975752,0.000123715,0.0001899725,0.00002251554,0.00004052098,0.00004581883,0.001515176,0.0003142449,0.04646696,0.78179,0.1693724],"study_design_scores_gemma":[0.00002460183,0.00003127192,0.0006491763,0.0002357585,0.00002163322,0.0001073594,0.00005212178,0.004720746,0.0004271265,0.153694,0.8400162,0.00001999371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001409174,0.01056268,0.06018482,0.00747391,0.01026835,0.00006982998,0.004268972,0.003538102,0.9022242],"genre_scores_gemma":[0.008231003,0.004654936,0.01299783,0.000854539,0.004199931,0.00007297082,0.003421047,0.002135115,0.9634327],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4723748,"threshold_uncertainty_score":0.7525933,"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."}}