{"id":"W2000444209","doi":"10.12957/cadinf.2009.6470","title":"Processo de Desenvolvimento do Sistema Multi-Agentes Monitor Glicêmico","year":2009,"lang":"pt","type":"article","venue":"Cadernos do IME - Série Informática","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science","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":[0.00186382,0.0005749174,0.0006098734,0.001424987,0.0007151118,0.003272258,0.0008817519,0.0007567662,0.004948608],"category_scores_gemma":[0.005177929,0.0003215552,0.0004693123,0.0008107608,0.0004050097,0.001534376,0.001075208,0.0008248558,0.00140588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006680902,"about_ca_system_score_gemma":0.00109439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004254918,"about_ca_topic_score_gemma":0.003158072,"domain_scores_codex":[0.9989523,0.0002479897,0.00009286268,0.0002202736,0.0004034859,0.00008305631],"domain_scores_gemma":[0.9982669,0.0005809178,0.0002057861,0.0003052087,0.0005303588,0.0001108087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001329125,0.0008038576,0.0366337,0.0009804292,0.0002539035,0.001017999,0.003577708,0.07872345,0.1167015,0.03032737,0.009472159,0.7201787],"study_design_scores_gemma":[0.0001561666,0.0008618345,0.02468819,0.0002866009,0.0003210161,0.0005718126,0.001808486,0.7497725,0.1265351,0.02484985,0.07001829,0.0001301864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2410838,0.00169511,0.711799,0.00148262,0.0003228936,0.0007892729,0.0007062174,0.01077273,0.03134832],"genre_scores_gemma":[0.8614663,0.0007130927,0.1230108,0.0002088988,0.00007295831,0.0002558831,0.0004960635,0.0002566816,0.01351938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004948608,"threshold_uncertainty_score":0.01655477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03145275467255462,"score_gpt":0.3055016043973951,"score_spread":0.2740488497248404,"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."}}