{"id":"W4236806283","doi":"10.21236/ada613247","title":"CNA's Integrated Ship Database: Third Quarter CY 2013 Update","year":2014,"lang":"en","type":"report","venue":"","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Database; Quarter (Canadian coin); Computer science; Geography; 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":[0.003861065,0.001532599,0.001505158,0.01019248,0.001009169,0.004523205,0.00303686,0.001342366,0.1198715],"category_scores_gemma":[0.01504197,0.0011641,0.001447444,0.01987682,0.0003870475,0.002964782,0.001872923,0.001740788,0.1336373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006579227,"about_ca_system_score_gemma":0.0225738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3592611,"about_ca_topic_score_gemma":0.2688288,"domain_scores_codex":[0.9965357,0.0001944138,0.0004437098,0.0002458302,0.002273677,0.0003067333],"domain_scores_gemma":[0.9844717,0.0007356621,0.0007672745,0.001130427,0.0122771,0.0006178025],"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":[0.0000379534,0.00001975333,0.0007114971,0.0000930778,0.000009301698,0.000007606485,0.00000594524,0.0001117848,0.0000266823,0.0001719462,0.9870396,0.01176479],"study_design_scores_gemma":[0.00003812623,0.00001279475,0.01504559,0.000174743,0.00003733546,0.00002974173,0.00003135256,0.0003426483,0.0002536717,0.0002396972,0.9837691,0.00002515027],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.000956394,0.0006898377,0.0008176376,0.001092989,0.001188447,0.0002184939,0.96452,0.00162256,0.02889354],"genre_scores_gemma":[0.002610595,0.002496361,0.002604896,0.0006189176,0.0002700415,0.0004582057,0.9118326,0.0008696464,0.0782387],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3592611,"threshold_uncertainty_score":0.7143399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01747111191196913,"score_gpt":0.2518287145842809,"score_spread":0.2343576026723118,"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."}}