{"id":"W279081550","doi":"","title":"사회연결망을 이용한 수산물 무역 네트워크 분석에 관한 연구","year":2013,"lang":"ko","type":"article","venue":"해양비즈니스","topic":"Nutrition, Health and Food Behavior","field":"Nursing","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Betweenness centrality; Centrality; Closeness; Order (exchange); Social network analysis; International trade; Business; Geography; Economy; Political science; Economics; Social capital; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007165113,0.0001764419,0.000182311,0.001812407,0.0008783073,0.001128832,0.0002107496,0.0002253005,0.006903553],"category_scores_gemma":[0.00345043,0.00008152532,0.0002353442,0.00248173,0.0003273845,0.001315393,0.0006461947,0.000240993,0.0004148635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009727293,"about_ca_system_score_gemma":0.001375861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0062676,"about_ca_topic_score_gemma":0.011667,"domain_scores_codex":[0.9995147,0.000166296,0.00003471773,0.00009192849,0.0001212237,0.00007118848],"domain_scores_gemma":[0.9978055,0.0009483875,0.0005327699,0.00006773803,0.0004820355,0.0001636041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001810754,0.0001931919,0.7306736,0.001204003,0.0001535193,0.001292746,0.02379093,0.00298243,0.00380113,0.03258668,0.009218582,0.1939222],"study_design_scores_gemma":[0.00001333472,0.0001849382,0.8453122,0.0005247581,0.0002091242,0.001389827,0.05713276,0.009933611,0.003225928,0.01382169,0.06820533,0.00004650358],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9166914,0.001446212,0.01310397,0.001616314,0.0000690365,0.0001431784,0.001214251,0.00005563858,0.06566004],"genre_scores_gemma":[0.9907786,0.000702278,0.003145925,0.0000703173,0.00001894504,0.00009577016,0.0004275041,0.000007847444,0.004752882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006903553,"threshold_uncertainty_score":0.02309471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02525218021179264,"score_gpt":0.3022817453296821,"score_spread":0.2770295651178894,"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."}}