{"id":"W1966910741","doi":"","title":"Semi-supervised learning of visual classifiers from web images and text","year":2009,"lang":"en","type":"article","venue":"International Joint Conference on Artificial Intelligence","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Discriminative model; Artificial intelligence; Generative model; Machine learning; Probabilistic logic; Object (grammar); Image (mathematics); Visualization; Generative grammar; Supervised learning; Information retrieval; Pattern recognition (psychology); Artificial neural network","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":[0.0002590884,0.0001917267,0.0002276398,0.0002309037,0.00009295392,0.0002854072,0.0007014677,0.00009369421,0.0002277459],"category_scores_gemma":[0.0002693249,0.0001799384,0.00008272263,0.0002431252,0.00017583,0.0004478411,0.0001198532,0.0002976453,0.00009034667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005000105,"about_ca_system_score_gemma":0.000106039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004555601,"about_ca_topic_score_gemma":0.000003249179,"domain_scores_codex":[0.9981703,0.00008751093,0.0005490849,0.0004911895,0.0004999442,0.0002019697],"domain_scores_gemma":[0.9988271,0.0001472681,0.0002387616,0.0002497518,0.0004360947,0.0001010245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003047311,0.0001182533,0.00006762072,0.000002194191,0.00001237936,0.000005529594,0.0002394821,0.00001305419,0.2487582,0.2779401,0.00004230572,0.4727704],"study_design_scores_gemma":[0.00004090919,0.000299474,0.001480957,0.0000929468,0.000004449922,0.000003895234,0.0002734439,0.3041332,0.6199489,0.07312359,0.000393384,0.0002049301],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03106266,0.00004522732,0.9514324,0.00687243,0.0003106903,0.0001555048,0.00001421138,0.0002325782,0.00987427],"genre_scores_gemma":[0.9912582,0.0002502516,0.007809529,0.0003482207,0.000078407,0.000007231024,0.00001067659,0.000006540463,0.0002309318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9601955,"threshold_uncertainty_score":0.7337674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06446601243891999,"score_gpt":0.3204279420706577,"score_spread":0.2559619296317377,"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."}}