{"id":"W4379528189","doi":"10.2139/ssrn.4452678","title":"Assessing the Effectiveness of Potential Protected Areas and OECMs in Conserving Biodiversity Against Subsurface Resource Extraction Impacts","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Biodiversity; Resource (disambiguation); Environmental resource management; Extraction (chemistry); Environmental science; Geography; Environmental planning; Natural resource economics; Ecology; Economics; Computer science; Biology; Chemistry","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":[0.007058921,0.0005467315,0.0004294644,0.001846707,0.0004292801,0.001789065,0.0008297766,0.0009770963,0.003193334],"category_scores_gemma":[0.02362478,0.000213099,0.0004975686,0.001423448,0.001037801,0.002778907,0.00165257,0.0005660094,0.0001501392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001650335,"about_ca_system_score_gemma":0.001442031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005485551,"about_ca_topic_score_gemma":0.01210001,"domain_scores_codex":[0.9967181,0.001814862,0.0001623801,0.0002395704,0.0006381833,0.0004268304],"domain_scores_gemma":[0.9786072,0.01583788,0.002519907,0.0006840563,0.001293276,0.001057698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006455567,0.002113829,0.4789129,0.000548955,0.0009514246,0.0002691477,0.0002666544,0.3184688,0.003055305,0.01159814,0.0006887264,0.1766704],"study_design_scores_gemma":[0.0004637157,0.01382084,0.5653973,0.0002749838,0.001101195,0.0002697128,0.003185611,0.3902787,0.005152745,0.01545678,0.004521069,0.00007732089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914056,0.0002263706,0.001892239,0.0002144432,0.00001049142,0.0001031446,0.0002788852,0.00001773888,0.005850955],"genre_scores_gemma":[0.9980738,0.00005505178,0.001485495,0.00001250938,0.000003316034,0.00002868217,0.00006589853,0.00000172803,0.0002735524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007058921,"threshold_uncertainty_score":0.03733158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009742001189398072,"score_gpt":0.233077285332918,"score_spread":0.2233352841435199,"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."}}