{"id":"W4309444825","doi":"10.1101/2022.11.20.515214","title":"Global connectivity and networks of marine reserves","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Coral and Marine Ecosystems Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Marine reserve; Environmental resource management; Natural resource economics; Business; Geography; Economic geography; Ecology; Economics; Biology; Habitat","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004536553,0.000163788,0.0001425569,0.001809694,0.0003386958,0.001125059,0.0002789893,0.0002819833,0.002765121],"category_scores_gemma":[0.004104704,0.0001290205,0.0002354551,0.001671899,0.0005478601,0.001436823,0.0007796617,0.0001909404,0.0001418177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005908275,"about_ca_system_score_gemma":0.0002083458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008923925,"about_ca_topic_score_gemma":0.006122055,"domain_scores_codex":[0.9998384,0.00006282352,0.000008407025,0.00004776992,0.00001765684,0.00002489689],"domain_scores_gemma":[0.9977334,0.001115445,0.0006693843,0.0001238534,0.0001928779,0.0001650676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002178559,0.00005402993,0.7375875,0.000148992,0.0003269534,0.0002916004,0.001302682,0.198534,0.00366229,0.0349277,0.002369552,0.02057703],"study_design_scores_gemma":[0.00003873751,0.00009564767,0.704816,0.0001264775,0.0001551507,0.0004357338,0.002639975,0.245238,0.001210518,0.03701573,0.008182444,0.00004554806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926875,0.0001327367,0.003541882,0.0002261738,0.000004266745,0.000008007475,0.0004763733,0.00002618281,0.002896899],"genre_scores_gemma":[0.998642,0.00007151681,0.0007314865,0.000008462872,0.000003405609,0.000006159037,0.0002802179,0.000005215505,0.0002515877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008923925,"threshold_uncertainty_score":0.01774395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052598854127021,"score_gpt":0.2057258911213415,"score_spread":0.1951999025800712,"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."}}