{"id":"W3125534413","doi":"","title":"Legal Liability for Environmental Harm from Deep Seabed Mining: Synthesis and Overview","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Balsillie School of International Affairs; University of Waterloo","funders":"","keywords":"Liability; Harm; Context (archaeology); Strict liability; Damages; Business; Environmental planning; Legal liability; Tort; Work (physics); Environmental resource management; Law; Political science; Engineering; Economics; Environmental science; Geography; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008371478,0.0001615536,0.0001694531,0.00002016813,0.0002719843,0.00007390769,0.0002855849,0.00006729015,0.002525813],"category_scores_gemma":[0.0001191614,0.0001489775,0.00008829787,0.0000406004,0.0002971194,0.0003426218,0.0001362555,0.0003500742,0.000175972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164308,"about_ca_system_score_gemma":0.00006802326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003827643,"about_ca_topic_score_gemma":0.001350498,"domain_scores_codex":[0.997979,0.00007512721,0.0002383728,0.0003251244,0.0003151836,0.001067169],"domain_scores_gemma":[0.9994282,0.0001999662,0.0001102898,0.0001532505,0.000008193786,0.0001000575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001208036,0.001067801,0.2633229,0.00002932861,0.001038473,0.00001863766,0.00192487,0.0000506467,0.05110337,0.1086541,0.001941213,0.5696407],"study_design_scores_gemma":[0.003032035,0.002222918,0.2393024,0.0001011309,0.0004269151,0.0007128475,0.002907629,0.009621764,0.02696262,0.4660242,0.2471402,0.001545275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922423,0.001327417,0.0011637,0.0007116578,0.0001508168,0.0001892571,0.00002789554,0.0000189932,0.004167928],"genre_scores_gemma":[0.9947422,0.0007818741,0.001718393,0.0002117255,0.0003823023,0.00001975469,0.000006260628,0.00002265104,0.002114863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5680954,"threshold_uncertainty_score":0.998386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008565390732162146,"score_gpt":0.2396018853064512,"score_spread":0.231036494574289,"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."}}