{"id":"W4393904469","doi":"10.48550/arxiv.2404.00408","title":"Deep Learning with Parametric Lenses","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Parametric statistics; Computer science; Optometry; Mathematics; Medicine; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001174358,0.0002393844,0.000216027,0.0004817065,0.0001325129,0.0002349242,0.0008151217,0.0002048361,0.00003866124],"category_scores_gemma":[0.00002769807,0.0002222961,0.0001218551,0.001066928,0.00005681876,0.0002270319,0.001667202,0.0009134025,0.0006362275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008299936,"about_ca_system_score_gemma":0.0001016663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006642148,"about_ca_topic_score_gemma":0.00001668731,"domain_scores_codex":[0.9984852,0.00009714238,0.0001097142,0.0009379653,0.0001008867,0.0002690604],"domain_scores_gemma":[0.9989907,0.000109904,0.0001165365,0.0005597256,0.0001070576,0.0001161389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000672364,0.0001371258,0.003145454,0.0004129709,0.000253981,0.00228904,0.0006742195,0.9079195,0.00007170271,0.05826372,0.001184861,0.02558016],"study_design_scores_gemma":[0.0003174795,0.000161731,0.0004433853,0.0004445814,0.0001069828,0.00001834658,0.0001848687,0.9430857,0.0004528094,0.05231745,0.001860718,0.0006059411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.449931,0.0003157832,0.5416754,0.0001064201,0.0004897414,0.0001773406,0.000002188792,0.0006258592,0.006676259],"genre_scores_gemma":[0.9939914,0.0002886644,0.002341227,0.00005677871,0.00004425433,0.000001159047,0.00001041937,0.00001692552,0.003249196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5440603,"threshold_uncertainty_score":0.9064972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05353749610784696,"score_gpt":0.1771303171505225,"score_spread":0.1235928210426756,"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."}}