{"id":"W4392387514","doi":"10.18280/ria.380115","title":"Machine Learning Prediction Model: A Case Study of Urban Transport of Medical and Pharmaceutical Products","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001405321,0.0007961619,0.0006419264,0.0008754414,0.0008907706,0.001236431,0.001376304,0.001850244,0.003823688],"category_scores_gemma":[0.002914569,0.0002052459,0.000839386,0.001256596,0.0006332524,0.0007878194,0.0009431567,0.001550895,0.0004626206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002301227,"about_ca_system_score_gemma":0.001164857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07029273,"about_ca_topic_score_gemma":0.04962813,"domain_scores_codex":[0.9995221,0.0002177231,0.00002192126,0.00009202741,0.00005707805,0.00008912121],"domain_scores_gemma":[0.9982061,0.001269465,0.0001167816,0.00007157763,0.0002605788,0.00007546294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002026846,0.0004450889,0.02906465,0.0001532873,0.00007316539,0.001662714,0.0002175461,0.9236774,0.0003867932,0.01469958,0.004336578,0.02508057],"study_design_scores_gemma":[0.00001131282,0.00004024889,0.002113102,0.00001097396,0.00001195303,0.00005005087,0.0001374882,0.9938373,0.0001956221,0.002517545,0.001065319,0.000009106051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8923428,0.001344226,0.08534337,0.006218373,0.0001929743,0.000246615,0.002447728,0.0003920998,0.01147172],"genre_scores_gemma":[0.9780021,0.0003839302,0.01576551,0.0001362444,0.00005168385,0.0001148136,0.0008826281,0.00002462943,0.004638371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07029273,"threshold_uncertainty_score":0.1397671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04957898056973763,"score_gpt":0.3283038334122186,"score_spread":0.2787248528424809,"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."}}