{"id":"W4252170826","doi":"10.21236/ada598997","title":"CNA's Integrated Ship Database: Fourth Quarter CY 2012 Update","year":2014,"lang":"en","type":"report","venue":"","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Database; Quarter (Canadian coin); Computer science; History; Archaeology","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":[0.003802328,0.001739657,0.001429422,0.01405094,0.0007297467,0.004120435,0.002874963,0.001196422,0.05070974],"category_scores_gemma":[0.01447293,0.00106164,0.001175336,0.02293009,0.0002953305,0.00311183,0.001815808,0.001313664,0.05477941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004757795,"about_ca_system_score_gemma":0.01589431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3171087,"about_ca_topic_score_gemma":0.2653521,"domain_scores_codex":[0.9968578,0.0002194502,0.0004870025,0.0002737386,0.00190433,0.0002577129],"domain_scores_gemma":[0.9858089,0.001012405,0.0009193038,0.001103159,0.01056577,0.0005903874],"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":[0.0001023292,0.00003316479,0.002425536,0.0002174049,0.0000276528,0.00001787397,0.00001357558,0.0002629283,0.00005860828,0.0002553577,0.9745388,0.02204682],"study_design_scores_gemma":[0.00005634881,0.00001622191,0.02531709,0.000264274,0.00007997492,0.0000670543,0.00004320813,0.0005068714,0.0004232833,0.0002429831,0.972953,0.00002959549],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001655371,0.001260652,0.000636892,0.0007825012,0.0005422764,0.0001204305,0.978227,0.001042225,0.01573249],"genre_scores_gemma":[0.003022909,0.00214248,0.001530094,0.0002855164,0.0001695159,0.0002367104,0.9577001,0.0004328764,0.03447992],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3171087,"threshold_uncertainty_score":0.6305259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937183317983405,"score_gpt":0.2545249013479615,"score_spread":0.2351530681681274,"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."}}