{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008290713,0.00004633732,0.00004460562,0.00005915282,0.0001692247,0.00006874183,0.0001836532,0.00001212636,0.000039698],"category_scores_gemma":[0.00002252072,0.00003526322,0.00001075779,0.0002060437,0.00001944112,0.001344246,0.00004821407,0.00005547422,0.0002603016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001073511,"about_ca_system_score_gemma":0.00003380937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000215246,"about_ca_topic_score_gemma":0.000002745364,"domain_scores_codex":[0.9995452,0.00001381575,0.0001015681,0.00006854527,0.0001644247,0.0001064968],"domain_scores_gemma":[0.9996924,0.000031752,0.00004782979,0.0001343903,0.00005131054,0.00004229487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002535951,0.00004349682,0.01927725,0.00002279795,0.00002797738,0.00005536262,0.02086776,0.009236248,0.0003310252,0.6410396,0.006715398,0.3023577],"study_design_scores_gemma":[0.001081639,0.000178935,0.06739298,0.00002029986,0.000001848201,0.0003719841,0.0004010997,0.630381,0.0004061736,0.000586301,0.2988015,0.0003762355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009340789,0.000002869946,0.879397,0.0003119799,0.00003436273,0.00003909276,8.791533e-8,0.0001900678,0.1106837],"genre_scores_gemma":[0.7838098,0.000001436374,0.2144146,0.0012237,0.0000111854,0.000002396875,0.000002195513,0.000001666955,0.000533035],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.774469,"threshold_uncertainty_score":0.3345737,"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."}}