{"id":"W7145023953","doi":"","title":"華人の東南アジア移民とシンガポール豐源號 (Wee Bin & Co.) の汽船","year":2020,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Marine and Coastal Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Southeast asia; China; Immigration; Heading (navigation); Middle East; Pacific ocean","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008341121,0.0004538359,0.000308351,0.002116646,0.001361793,0.003327138,0.0003349725,0.0005768272,0.5178209],"category_scores_gemma":[0.002348721,0.0002658491,0.000144028,0.003061473,0.0004944039,0.002702375,0.001104735,0.0007934224,0.483381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006978013,"about_ca_system_score_gemma":0.001453286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005451247,"about_ca_topic_score_gemma":0.01101393,"domain_scores_codex":[0.9995912,0.00003024146,0.00004843147,0.00007704788,0.0002226947,0.00003046505],"domain_scores_gemma":[0.9982353,0.0002768114,0.000113016,0.0002109466,0.000798993,0.000364922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004583836,0.00004240762,0.001423135,0.0001617257,0.000003325359,0.000114961,0.0001214016,0.00006040839,0.001042263,0.002182037,0.5444947,0.4503079],"study_design_scores_gemma":[0.000003496644,0.00001085892,0.001371975,0.00004746508,0.000002284407,0.00007515558,0.0001062305,0.00009406694,0.0005610757,0.0003155926,0.9974062,0.00000558484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003861231,0.005060842,0.003543778,0.005750254,0.002111784,0.0002295999,0.007261364,0.003012505,0.9691686],"genre_scores_gemma":[0.008852651,0.004790735,0.002285172,0.000708974,0.0003338379,0.00006957803,0.003810613,0.0004267568,0.9787217],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5178209,"threshold_uncertainty_score":0.6877699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03537198871228681,"score_gpt":0.2792085782089814,"score_spread":0.2438365894966946,"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."}}