{"id":"W4408820251","doi":"10.58837/chula.the.2023.504","title":"Strengthening China's response to economic losses caused byship oil pollution: advancing compensation mechanisms","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Oil pollution; Compensation (psychology); Harm; Legislature; Business; Oil spill; Environmental planning; Pollution; Mechanism (biology); Human settlement; Natural resource economics; Environmental protection; Environmental resource management; Political science; Engineering; Environmental science; Economics; Law; Ecology; Waste management","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":[0.003837693,0.0002751198,0.000174817,0.001722257,0.00227268,0.003265748,0.0008982298,0.001725675,0.002213887],"category_scores_gemma":[0.00343887,0.0001443878,0.0003143013,0.001128183,0.002026239,0.002366464,0.002154836,0.001318013,0.0001533865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006079942,"about_ca_system_score_gemma":0.02489239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04504189,"about_ca_topic_score_gemma":0.05908059,"domain_scores_codex":[0.9984702,0.0003403448,0.00009658244,0.0001358755,0.0005250638,0.0004319083],"domain_scores_gemma":[0.9985465,0.0003339075,0.0002390888,0.0001184058,0.0005832168,0.0001787941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009611528,0.0002691346,0.06038544,0.001107058,0.0001000936,0.0009474203,0.01064307,0.007816256,0.006831687,0.5657131,0.03024318,0.3158474],"study_design_scores_gemma":[0.0001252869,0.0004806808,0.2046311,0.001792506,0.0002954097,0.0003542833,0.01562335,0.01705627,0.01172078,0.08174991,0.6659615,0.000208976],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6251173,0.01749681,0.01104175,0.0862047,0.0009333644,0.0003757954,0.0001456739,0.0001742404,0.2585103],"genre_scores_gemma":[0.9712855,0.007148377,0.003092724,0.003232467,0.0001748682,0.00007009268,0.00005811846,0.000009539429,0.01492827],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04504189,"threshold_uncertainty_score":0.08955944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008410351001356781,"score_gpt":0.2601871277310991,"score_spread":0.2517767767297424,"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."}}