{"id":"W6986497710","doi":"","title":"POLICY IMPLICATIONS OF MANAGING BIODIVERSITY AND NATURAL RESOURCES ACROSS INTERNATIONAL BOUNDARIES","year":2022,"lang":"en","type":"article","venue":"Aquila Digital Community (University of Southern Mississippi)","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fisheries management; Fisheries law; Natural resource; Resource management (computing); Fisheries science; Set (abstract data type); Boundary (topology); Public policy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002164604,0.0000828031,0.0001306158,0.00007466033,0.001754741,0.00009041496,0.0009311567,0.00002519014,0.001808149],"category_scores_gemma":[0.00004077799,0.0001018226,0.00006745972,0.0003078875,0.001402951,0.0003466989,0.004491693,0.0003270255,0.0000166438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001070018,"about_ca_system_score_gemma":0.00002432707,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01432388,"about_ca_topic_score_gemma":0.0006437537,"domain_scores_codex":[0.9992256,0.00009889903,0.0000928611,0.0001295259,0.0002824345,0.0001706616],"domain_scores_gemma":[0.9994017,0.0000687725,0.0001116905,0.0003145827,0.00002476391,0.00007851719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002201814,0.0002416828,0.8745164,0.00002674257,0.00008717759,0.000004624425,0.04886154,0.00002326209,0.0005017326,0.0001705942,0.0009980749,0.07434803],"study_design_scores_gemma":[0.0009055221,0.0001929914,0.3969844,0.000008157593,0.00002170812,0.00001955279,0.3210587,0.0002440896,0.00002681597,0.003646847,0.2765634,0.0003278402],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9306949,0.00000893733,0.00002469765,0.002234933,0.00001468937,0.00006634917,0.0009507782,0.00001973308,0.06598499],"genre_scores_gemma":[0.9965656,0.000008644625,0.00008541113,0.00004821568,0.000004082126,2.015712e-7,0.00007551757,0.00000397377,0.00320831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.477532,"threshold_uncertainty_score":0.9995449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542885869006284,"score_gpt":0.2313358274231475,"score_spread":0.2159069687330846,"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."}}