{"id":"W3011056391","doi":"","title":"Optimizing color information processing inside an SVM network","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Berger (Canada)","funders":"","keywords":"Support vector machine; Computer science; Artificial intelligence; Pattern recognition (psychology); Data mining","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":[0.002666034,0.0001656443,0.0001638645,0.0001139471,0.0004110513,0.0005088224,0.001145493,0.00008753273,0.00001716752],"category_scores_gemma":[0.0008032769,0.0001336563,0.00005759784,0.0006156967,0.0001132987,0.004328829,0.0004634161,0.0001356593,0.00003741351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000828805,"about_ca_system_score_gemma":0.0001362205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004301713,"about_ca_topic_score_gemma":0.00006410998,"domain_scores_codex":[0.9975951,0.001057973,0.0003695988,0.0003400507,0.000290104,0.0003471848],"domain_scores_gemma":[0.9965883,0.0005011411,0.0003061361,0.001101923,0.00135337,0.0001491031],"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":[0.000006621603,0.00007443073,0.0002761174,0.0000167959,0.000005785986,0.000001837531,0.003054684,0.00003594822,0.004309111,0.101607,0.0004099449,0.8902017],"study_design_scores_gemma":[0.00146421,0.000006175086,0.003619748,0.002497268,0.00002040859,0.00005116883,0.000145671,0.1230797,0.6660516,0.0404492,0.1614889,0.001125874],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005816542,0.0002272531,0.9765253,0.003920401,0.00006051155,0.0002007019,0.000002633356,0.000681671,0.012565],"genre_scores_gemma":[0.4335377,0.0001542505,0.5653027,0.0003078179,0.00001823282,0.00002471981,0.00001333748,0.00001164213,0.0006296425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8890758,"threshold_uncertainty_score":0.5450345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126646923524344,"score_gpt":0.2403703971407008,"score_spread":0.2277057047882664,"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."}}