{"id":"W2805580942","doi":"10.1126/sciadv.aar5237","title":"Corporate control and global governance of marine genetic resources","year":2018,"lang":"en","type":"article","venue":"Science Advances","topic":"International Maritime Law Issues","field":"Environmental Science","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"Nippon Foundation; Svenska Forskningsrådet Formas; Stiftelsen för Miljöstrategisk Forskning; Walton Family Foundation; Familjen Erling-Perssons Stiftelse; Gordon and Betty Moore Foundation; Styrelsen för Internationellt Utvecklingssamarbete; David and Lucile Packard Foundation","keywords":"Corporate governance; Corporation; Genetic resources; Business; Control (management); Biology; Computer science; Biotechnology; Finance; Artificial intelligence","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.000200646,0.00007190048,0.00008913846,0.000009291389,0.000125502,0.00002835396,0.0003828673,0.00001316077,0.0005568361],"category_scores_gemma":[0.00009402053,0.00006050203,0.00001162063,0.0003356786,0.003804994,0.0005075423,0.0002400207,0.00002445838,0.0000990108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006471004,"about_ca_system_score_gemma":0.00001210332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004208239,"about_ca_topic_score_gemma":0.0004687948,"domain_scores_codex":[0.9989146,0.00001299653,0.0001335606,0.0002768436,0.0004723365,0.000189663],"domain_scores_gemma":[0.999574,0.00002423787,0.000168864,0.0001367546,0.00003651986,0.000059638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004496588,0.00002508058,0.9176294,0.000004992116,0.000002572312,0.000003974841,0.00009031717,0.0001757889,0.02199397,0.005407502,0.00006132884,0.05456007],"study_design_scores_gemma":[0.0002035146,0.0001496973,0.9595991,0.0000107161,0.00000332003,0.00001127087,0.00001992283,0.0005913656,0.008607355,0.02187954,0.008832393,0.00009179352],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577461,0.0002047863,0.0001128983,0.0001844248,0.0001284048,0.00007315916,0.00001081724,0.00001259501,0.04152678],"genre_scores_gemma":[0.9937834,0.00002542881,0.005552417,0.0001536178,0.00004361706,0.000002861163,1.576572e-7,0.000002323908,0.0004362189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05446828,"threshold_uncertainty_score":0.9989061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004959408237534272,"score_gpt":0.2318399530024759,"score_spread":0.2268805447649416,"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."}}