{"id":"W4246316082","doi":"10.31219/osf.io/fe4dg","title":"PEMBUATAN APLIKASI SISTEM PAKAR UNTUK DIAGNOSA PENYAKIT MATA PADA MANUSIA BERBASIS WEB","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Computer science; Forward chaining; Expert system; Unified Modeling Language; Artificial intelligence; Software; World Wide Web; Programming language","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":[0.001228152,0.001030201,0.0008466291,0.001485837,0.000897003,0.005921965,0.0009134415,0.001327119,0.03254835],"category_scores_gemma":[0.003638322,0.0004930118,0.0006665406,0.001200131,0.0004844691,0.003715751,0.001595628,0.001360746,0.02754501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005711844,"about_ca_system_score_gemma":0.0009896264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001856626,"about_ca_topic_score_gemma":0.00119135,"domain_scores_codex":[0.9988997,0.0002025243,0.0001114955,0.0002369656,0.0004367951,0.0001125128],"domain_scores_gemma":[0.9981176,0.0005485357,0.00008322247,0.0004306615,0.0006824551,0.0001375665],"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":[0.001171458,0.0006846475,0.008194252,0.001428514,0.0001652652,0.002027981,0.001606039,0.003630024,0.0386822,0.01774555,0.08337624,0.8412877],"study_design_scores_gemma":[0.0001820818,0.0003910372,0.01312926,0.0007208343,0.0003230845,0.005300285,0.001741581,0.05603883,0.08760036,0.02984338,0.8045416,0.0001876289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1035195,0.009402236,0.4214197,0.005923372,0.00181853,0.001145784,0.006724323,0.1323648,0.3176816],"genre_scores_gemma":[0.4342938,0.008628915,0.2765859,0.001961762,0.0008955964,0.0006273761,0.01550356,0.009486874,0.2520162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03254835,"threshold_uncertainty_score":0.108885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839368133277913,"score_gpt":0.2665857923491171,"score_spread":0.2381921110163379,"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."}}