{"id":"W4411161784","doi":"10.35965/ursj.v7i2.6216","title":"Prediksi Kebutuhan Kapasitas Dermaga Berdasarkan Tren Perubahan Pola Penyeberangan","year":2025,"lang":"id","type":"article","venue":"Urban and Regional Studies Journal","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","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":[0.0009442947,0.0004812255,0.0004525401,0.001190545,0.00123155,0.003225428,0.0005296317,0.0006363513,0.02150148],"category_scores_gemma":[0.002308434,0.0003697962,0.0005138539,0.002828184,0.0006811111,0.001933299,0.00160321,0.0009482111,0.003294002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500786,"about_ca_system_score_gemma":0.002606497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04191927,"about_ca_topic_score_gemma":0.06694089,"domain_scores_codex":[0.9993136,0.0001589835,0.00003831898,0.0001693348,0.0001775033,0.0001422272],"domain_scores_gemma":[0.998669,0.0003633738,0.0002562697,0.0001039572,0.00050628,0.0001010092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006722508,0.0002547037,0.6037825,0.003914979,0.000580944,0.002874502,0.02001612,0.002459641,0.01228692,0.01648567,0.0356394,0.3010325],"study_design_scores_gemma":[0.00002770156,0.0001776553,0.7016847,0.0008868652,0.0002376772,0.0008957973,0.02692701,0.001231368,0.003898157,0.002849603,0.2610961,0.00008737028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8385764,0.01502111,0.01062113,0.008486727,0.0003194578,0.0002464865,0.01726659,0.0004718879,0.1089902],"genre_scores_gemma":[0.9278855,0.007146491,0.005257257,0.0006086773,0.00009586003,0.0001951176,0.006308022,0.0001141636,0.0523889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04191927,"threshold_uncertainty_score":0.08335054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02507421055560586,"score_gpt":0.2660113153824094,"score_spread":0.2409371048268035,"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."}}