{"id":"W4361866068","doi":"10.4230/lipics.icalp.2023.42","title":"Online Learning and Disambiguations of Partial Concept Classes","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Learnability; Class (philosophy); Extension (predicate logic); Computer science; Mathematics; Theoretical computer science; Artificial intelligence; Discrete mathematics; Programming language","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":[0.0001494929,0.0001645986,0.0002471261,0.0001574311,0.0001349374,0.00005960943,0.0005722711,0.0001287938,0.0000139786],"category_scores_gemma":[0.0001206017,0.0001851212,0.00009377122,0.0003693228,0.000133323,0.0001292505,0.001357445,0.0006015272,0.00001359873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000261235,"about_ca_system_score_gemma":0.00008315792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003031741,"about_ca_topic_score_gemma":0.00002663911,"domain_scores_codex":[0.9988115,0.0001620967,0.0001590671,0.0006037864,0.00007567248,0.0001879002],"domain_scores_gemma":[0.9990325,0.0002036579,0.0002163113,0.0003722128,0.00008519517,0.00009009798],"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":[0.00000907686,0.0001693776,0.03143161,0.0001150327,0.000130301,0.0001338221,0.001203649,0.8515639,0.00003683441,0.1062481,0.0001858344,0.008772472],"study_design_scores_gemma":[0.0002590566,0.00006296163,0.008271982,0.00007971098,0.0000374548,0.000001667804,0.0001767016,0.9829417,0.00004280432,0.007128668,0.0007779158,0.0002193627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.365422,0.00006227905,0.6330799,0.0002848485,0.0004091253,0.0001009544,0.00002282717,0.0003360889,0.0002819712],"genre_scores_gemma":[0.9932886,0.0001511134,0.002436954,0.00001343263,0.00008467118,3.282175e-7,0.00004171464,0.00001215323,0.003971013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.630643,"threshold_uncertainty_score":0.7549022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07790816076508807,"score_gpt":0.2334005466304579,"score_spread":0.1554923858653698,"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."}}