{"id":"W647361811","doi":"","title":"03 - Segmentation d'images couleur par partitions de Voronoï","year":2004,"lang":"fr","type":"article","venue":"Traitement du signal","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Segmentation; Mathematics; Artificial intelligence; Computer science; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005583975,0.00024639,0.0001868366,0.00009621638,0.000349399,0.0003658691,0.0004510325,0.0001136066,0.0009999211],"category_scores_gemma":[0.00002092708,0.0002655601,0.0001380236,0.000395011,0.0002476149,0.00106281,0.00007780088,0.0002036843,0.0005166737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004024962,"about_ca_system_score_gemma":0.0003616875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001534604,"about_ca_topic_score_gemma":0.00001257804,"domain_scores_codex":[0.9979583,0.0001601628,0.000474999,0.0004420922,0.000438818,0.0005256103],"domain_scores_gemma":[0.9990599,0.00005563565,0.0001856873,0.0003010097,0.0001906766,0.0002071082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006769205,0.003323179,0.001573725,0.0003677759,0.0002247162,0.000185856,0.007364042,0.001879742,0.3299517,0.3141542,0.02534513,0.3155622],"study_design_scores_gemma":[0.001705652,0.0006897521,0.016026,0.0002664521,0.000125786,0.00009430358,0.0003074854,0.006121693,0.8873378,0.04277541,0.04387422,0.0006754617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008074353,0.001217476,0.9659567,0.02134141,0.0003737547,0.0004570933,0.00006209886,0.0003180619,0.002199023],"genre_scores_gemma":[0.9192924,0.000619952,0.07516042,0.001658617,0.0004507185,0.0001684888,0.00005550702,0.00002583565,0.002568063],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.911218,"threshold_uncertainty_score":0.9999797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03340675211585999,"score_gpt":0.2774120870275026,"score_spread":0.2440053349116426,"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."}}