{"id":"W2146250995","doi":"10.5555/2627435.2697064","title":"Recursive teaching dimension, VC-dimension and sample compression","year":2014,"lang":"en","type":"article","venue":"Journal of Machine Learning Research","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of Alberta","funders":"","keywords":"Dimension (graph theory); VC dimension; Intersection (aeronautics); Mathematics; Matching (statistics); Concept class; Class (philosophy); Bounded function; Sample (material); Theoretical computer science; Discrete mathematics; Computer science; Algorithm; Combinatorics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.002490527,0.0007672342,0.001212714,0.002169978,0.00133725,0.004016347,0.001940919,0.001469132,0.005919273],"category_scores_gemma":[0.02405785,0.0004869319,0.001005515,0.002055084,0.004658222,0.007648393,0.002881134,0.003591542,0.0005285849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003215333,"about_ca_system_score_gemma":0.001245235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009872763,"about_ca_topic_score_gemma":0.0009988087,"domain_scores_codex":[0.9971269,0.0007582843,0.0001388538,0.000690925,0.000874312,0.0004108532],"domain_scores_gemma":[0.9694579,0.02273442,0.001582879,0.004043048,0.00103116,0.001150555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001404542,0.0000676516,0.002921507,0.0001802225,0.00003371622,0.00008475358,0.0002631845,0.03537169,0.00151653,0.9139168,0.002597356,0.04290624],"study_design_scores_gemma":[0.00003549369,0.00007136706,0.001074096,0.00006113455,0.00002521206,0.0002343848,0.000071709,0.135062,0.002217383,0.8558816,0.005220465,0.00004528344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2631215,0.003619595,0.6933656,0.003005448,0.0001071086,0.0002132439,0.00164657,0.001184783,0.03373607],"genre_scores_gemma":[0.9083623,0.001201456,0.08318546,0.0004219378,0.0002464681,0.0003888314,0.001125076,0.0002335651,0.004834779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005919273,"threshold_uncertainty_score":0.02332896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693260769113972,"score_gpt":0.345164434175636,"score_spread":0.3182318264844963,"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."}}