{"id":"W2118099541","doi":"10.1145/1390156.1390203","title":"Boosting with incomplete information","year":2008,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Boosting (machine learning); Computer science; Artificial intelligence; Classifier (UML); Machine learning; Cognitive neuroscience of visual object recognition; Pattern recognition (psychology); Feature extraction","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":[0.007099749,0.001234648,0.003369084,0.0009314442,0.0006684621,0.001460819,0.002255346,0.001540739,0.00125892],"category_scores_gemma":[0.01257698,0.0008738534,0.001095396,0.0009046169,0.001787328,0.002921189,0.002308215,0.002113967,0.000658597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008891688,"about_ca_system_score_gemma":0.000918488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005398348,"about_ca_topic_score_gemma":0.0004775365,"domain_scores_codex":[0.9972186,0.001586134,0.00008715513,0.0003468258,0.0005876066,0.0001736657],"domain_scores_gemma":[0.9951166,0.002640872,0.0002980952,0.0009044196,0.0008142995,0.0002257311],"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":[0.0003495574,0.0001515255,0.001675857,0.0003129924,0.0002467038,0.0001718543,0.0001893181,0.6808643,0.004506609,0.1344844,0.005534416,0.1715125],"study_design_scores_gemma":[0.00001830722,0.00005449985,0.0001504296,0.00001458013,0.00001967468,0.00004026735,0.000006785433,0.9433685,0.0009786339,0.05414752,0.001190282,0.00001057361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009227035,0.000435624,0.9889271,0.0002009186,0.00004275046,0.00003050823,0.00003006987,0.0001942999,0.000911688],"genre_scores_gemma":[0.5744652,0.0007949994,0.4193074,0.0007677349,0.0003539732,0.0002768192,0.000466393,0.0001849271,0.00338249],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007099749,"threshold_uncertainty_score":0.03754753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759088385830544,"score_gpt":0.1856703410899095,"score_spread":0.1680794572316041,"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."}}