{"id":"W2909057070","doi":"10.30659/jpsa.v14i1.3856","title":"DAMPAK TERMINAL MANGKANG KOTA SEMARANG DAN PERMASALAHAN DI KAWASAN SEKITARNYA STUDI KASUS : TERMINAL MANGKANG SEMARANG","year":2019,"lang":"en","type":"article","venue":"Jurnal Planologi","topic":"Urban Transport Systems Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Terminal (telecommunication); Transport engineering; Computer science; Operations research; Telecommunications; Engineering","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"],"consensus_categories":[],"category_scores_codex":[0.0007029619,0.0007875821,0.001119324,0.0005623162,0.0002216922,0.0001696126,0.0008550903,0.0004375806,0.0002289486],"category_scores_gemma":[0.00002926045,0.0007242737,0.0004956007,0.0005516585,0.00008635518,0.0005422051,0.0001133218,0.0009684745,0.0004871191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000324084,"about_ca_system_score_gemma":0.00005145296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002628956,"about_ca_topic_score_gemma":0.0005426431,"domain_scores_codex":[0.9960442,0.0001718343,0.001005061,0.0007819019,0.0007626718,0.001234387],"domain_scores_gemma":[0.9982015,0.000197376,0.0002359079,0.0009646881,0.00008306605,0.0003174802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003101995,0.0002260717,0.9208772,0.001317916,0.00187349,0.005111844,0.001858694,0.007120432,0.04946075,0.0001797214,0.004530115,0.00713352],"study_design_scores_gemma":[0.002978746,0.0006073702,0.940503,0.0008668078,0.000985698,0.002176618,0.004543826,0.02482997,0.003108556,0.00003565914,0.01676853,0.002595227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902201,0.001131446,0.0003482405,0.0001070366,0.001134953,0.0005525633,0.00009911919,0.0007625899,0.00564401],"genre_scores_gemma":[0.9966514,0.00006000451,0.000266676,0.00007964291,0.0006223546,0.00005470543,0.0001527056,0.0001482238,0.001964358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04635219,"threshold_uncertainty_score":0.9995208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00801709149894173,"score_gpt":0.1996132049050709,"score_spread":0.1915961134061292,"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."}}