{"id":"W4385432345","doi":"10.35724/mjti.v5i02.5322","title":"IMPLEMENTASI TEKNOLOGI E-MARKET UNTUK MENINGKATKAN LAYANAN PERDAGANGAN TERNAK","year":2023,"lang":"id","type":"article","venue":"Musamus Journal of Technology & Information","topic":"Information Retrieval and Data Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Physics; Humanities","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003272257,0.0004119147,0.000611806,0.003992571,0.0005525567,0.0006249871,0.002463538,0.0005483615,0.0002742718],"category_scores_gemma":[0.001017595,0.0003650862,0.0002640259,0.003673245,0.0002538433,0.008507671,0.001141346,0.001121295,0.001403145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002990178,"about_ca_system_score_gemma":0.0004247445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001696316,"about_ca_topic_score_gemma":0.000008250287,"domain_scores_codex":[0.9953649,0.0001162037,0.002433669,0.0002094542,0.0009847516,0.000891039],"domain_scores_gemma":[0.9953221,0.0001664117,0.002624793,0.0007505283,0.0009477186,0.0001884336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003137473,0.0001240605,0.01001697,0.0003411697,0.0005993557,0.0003887335,0.01071075,0.0002134449,0.0009705081,0.02919037,0.2150354,0.7320955],"study_design_scores_gemma":[0.003668378,0.002206968,0.01071642,0.000513513,0.0001556699,0.00332563,0.01383076,0.02261876,0.01004574,0.00231793,0.9296438,0.0009564317],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7700617,0.000827476,0.1240221,0.03458194,0.01213083,0.001629393,0.0004607302,0.002310336,0.05397543],"genre_scores_gemma":[0.9835102,0.0009563072,0.01238294,0.00154758,0.0003173672,0.0000169135,0.0001916539,0.00002959313,0.001047417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7311391,"threshold_uncertainty_score":0.9998801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0154137811139985,"score_gpt":0.2625879107056917,"score_spread":0.2471741295916932,"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."}}