{"id":"W4383823826","doi":"10.11159/iccste23.210","title":"Maritime Transport Infrastructure Effects on the Territory Development","year":2023,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport infrastructure; Computer science; Business; Transport engineering; Engineering","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":[0.0002346398,0.0001645701,0.0001144316,0.0008437462,0.001317431,0.003408524,0.0002764596,0.0003509784,0.01362885],"category_scores_gemma":[0.000999426,0.0000950175,0.0003226262,0.001203727,0.001652899,0.001230281,0.002701423,0.0005870059,0.0006153724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002936447,"about_ca_system_score_gemma":0.002590218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02827736,"about_ca_topic_score_gemma":0.04270334,"domain_scores_codex":[0.9995254,0.0001411084,0.00001783117,0.00005097807,0.00007701997,0.0001876218],"domain_scores_gemma":[0.9993387,0.0001212525,0.0001713284,0.00003870086,0.0001696321,0.0001603799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003831072,0.0004645207,0.5035372,0.000670591,0.0002231863,0.01840838,0.03998477,0.01690942,0.01231096,0.2580409,0.01078278,0.1382842],"study_design_scores_gemma":[0.000009051373,0.0002877147,0.7667717,0.000352079,0.000121766,0.002075449,0.1015364,0.002874851,0.002891932,0.00626554,0.1167683,0.00004531803],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8088424,0.0005525758,0.0006681603,0.001170599,0.00002870811,0.00003202554,0.0002224547,0.00002327627,0.1884597],"genre_scores_gemma":[0.993542,0.0004426586,0.0001212657,0.00002132484,0.00000525337,0.000007876967,0.00005039665,0.000004931687,0.005804399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02827736,"threshold_uncertainty_score":0.05622554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0147279204219968,"score_gpt":0.2454274445852159,"score_spread":0.2306995241632191,"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."}}