{"id":"W2259495747","doi":"10.35585/inspir.v4i2.47","title":"Penerapan Sistem Pakar Dalam Mendiagnosa Penyakit Ikan Bandeng Dengan Metode Forward Chaining","year":2014,"lang":"id","type":"article","venue":"","topic":"Information Retrieval and Data Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Forward chaining; Backward chaining; Physics; Computer science; Inference engine; Expert system; Artificial intelligence","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":[0.0003653183,0.001170881,0.0006576493,0.001000155,0.001034267,0.001994537,0.0005691449,0.0008021853,0.01556017],"category_scores_gemma":[0.0003697251,0.0004808274,0.0007914723,0.0009109167,0.0005586139,0.001258289,0.0008371965,0.001596795,0.004945869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008296884,"about_ca_system_score_gemma":0.0008230559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003070127,"about_ca_topic_score_gemma":0.00484629,"domain_scores_codex":[0.9996309,0.00003352686,0.00002069444,0.0001132194,0.0001414853,0.00006012775],"domain_scores_gemma":[0.9997304,0.00004353625,0.00004162689,0.00004372904,0.0000904235,0.0000502439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005091705,0.0001725078,0.001710183,0.001023274,0.00006608749,0.001203507,0.0003752212,0.0007943008,0.8972391,0.003230553,0.001908949,0.09176709],"study_design_scores_gemma":[0.00006135664,0.0009002022,0.01340936,0.0003858367,0.0002469002,0.002205327,0.0009150806,0.002291513,0.6921553,0.00297895,0.2843394,0.0001107467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6663797,0.03015997,0.08634248,0.002157339,0.001635769,0.0008357093,0.003682768,0.002998395,0.2058077],"genre_scores_gemma":[0.7023661,0.01159622,0.05748069,0.001075318,0.0001328357,0.0003207765,0.003076112,0.0005401936,0.2234117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01556017,"threshold_uncertainty_score":0.05205399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017416730041111,"score_gpt":0.2396499651378759,"score_spread":0.2222332350967649,"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."}}