{"id":"W6910742329","doi":"10.48660/23050101","title":"Industry Speaker Presentations","year":2023,"lang":"en","type":"other","venue":"PIRSA","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute; IBM (Canada)","funders":"","keywords":"Set (abstract data type); Focus (optics); Feature (linguistics); Perspective (graphical)","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":["insufficient_payload"],"category_scores_codex":[0.00006479051,0.0001896709,0.0001778104,0.0003255456,0.00002364006,0.00003169803,0.0002029163,0.0009933752,0.04223038],"category_scores_gemma":[0.00008925886,0.0001943891,0.00006291945,0.0004153355,0.00005889217,0.00003061966,0.00007697274,0.0008791002,0.2911603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004819862,"about_ca_system_score_gemma":0.00006235424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001076622,"about_ca_topic_score_gemma":0.00318431,"domain_scores_codex":[0.9990405,0.00003692657,0.0001198952,0.0002772477,0.0002818242,0.0002436336],"domain_scores_gemma":[0.9992796,0.00003762214,0.0001198535,0.0004623308,0.00001587278,0.00008475881],"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":[9.62141e-7,0.0000227839,0.002089103,0.0000136905,0.00008754039,0.00002729965,0.00004112341,0.000002926738,0.00001184934,0.000324723,0.9968338,0.0005442117],"study_design_scores_gemma":[0.0001519181,0.000003280208,0.003391013,0.00008205245,0.00005059829,0.000002034198,0.00003265701,0.000004798688,0.000009944067,0.00006501134,0.9960068,0.0001998985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002793346,0.0001399696,0.000004186341,0.0001502119,0.0006128549,0.0002678554,0.0006702491,0.003108501,0.9950182],"genre_scores_gemma":[0.000217906,0.00001370927,0.0001032799,0.00004846938,0.001212606,0.0000576649,0.0001092335,0.005130732,0.9931064],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2489299,"threshold_uncertainty_score":0.9586452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689691124266392,"score_gpt":0.3256923037595513,"score_spread":0.2787953925168873,"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."}}