{"id":"W2160257818","doi":"10.3115/1119212.1119220","title":"Why can't José read?","year":2003,"lang":"en","type":"article","venue":"","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Object (grammar); Set (abstract data type); Process (computing); Context (archaeology); Mobile robot; Robot; Image (mathematics); Computer vision; Cognitive neuroscience of visual object recognition; Spatial contextual awareness; Pattern recognition (psychology)","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":[0.001197971,0.0004215394,0.0005298965,0.0004657746,0.002292732,0.00341209,0.001248165,0.002845431,0.01568328],"category_scores_gemma":[0.01062318,0.0003071967,0.000423032,0.001103079,0.002889758,0.007384222,0.001133526,0.001932108,0.00585815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008405445,"about_ca_system_score_gemma":0.0008126504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008447344,"about_ca_topic_score_gemma":0.01306738,"domain_scores_codex":[0.9992424,0.0002110996,0.00002586818,0.0002811798,0.0001280305,0.0001114737],"domain_scores_gemma":[0.995365,0.003084024,0.000441082,0.0002979613,0.0004394156,0.0003725211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006453093,0.0002940079,0.01362412,0.0008833798,0.0001023348,0.002633795,0.005924914,0.01023286,0.003522502,0.3432243,0.2271291,0.3917834],"study_design_scores_gemma":[0.00005746243,0.0001956134,0.004248033,0.0001778636,0.00007927508,0.001931959,0.006459979,0.04225264,0.003695271,0.5831026,0.3576942,0.0001052374],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2089101,0.02197356,0.3161147,0.2019778,0.006135439,0.0002380333,0.002801072,0.002264571,0.2395848],"genre_scores_gemma":[0.7584183,0.008948209,0.09242607,0.013212,0.001975036,0.0001250643,0.001830829,0.0006487376,0.1224157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01568328,"threshold_uncertainty_score":0.05246574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01224074151005225,"score_gpt":0.2586873306050244,"score_spread":0.2464465890949722,"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."}}