{"id":"W4251718986","doi":"10.5539/enrr.v10n1p71","title":"Reviewer Acknowledgements for Environment and Natural Resources Research, Vol. 10, No. 1","year":2020,"lang":"en","type":"article","venue":"Environment and Natural Resources Research","topic":"Regional Development and Environment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural (archaeology); Engineering ethics; Natural resource; Environmental ethics; Library science; Political science; Computer science; Geography; Philosophy; Engineering; Archaeology; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004889532,0.0003716366,0.0004392947,0.0002582117,0.002501474,0.0003255009,0.0007428249,0.0002380448,0.002650236],"category_scores_gemma":[0.007018485,0.0003126881,0.0001359603,0.0003367708,0.002583514,0.0003502759,0.001202159,0.001117678,0.001995989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004311541,"about_ca_system_score_gemma":0.00004609404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006679492,"about_ca_topic_score_gemma":0.0000222603,"domain_scores_codex":[0.9926625,0.001157486,0.0004828761,0.001179198,0.003044526,0.001473415],"domain_scores_gemma":[0.9971495,0.001112655,0.0001069451,0.0003479431,0.0005150646,0.0007679226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00118197,0.0002945071,0.01379094,0.0004181515,0.0002730619,0.00002672222,0.0356002,0.0000167857,0.002185942,0.0004457808,0.8417866,0.1039794],"study_design_scores_gemma":[0.0007841103,0.0003286766,0.01856349,0.00008162025,0.00001786098,2.70794e-7,0.002291192,0.0002357374,0.0001122107,0.0003468331,0.9768613,0.0003767261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8808308,0.08081944,0.00002296627,0.01938066,0.001792737,0.005261519,0.00003976154,0.0001147608,0.01173735],"genre_scores_gemma":[0.4832167,0.1116177,0.001984397,0.001026938,0.009011194,0.0008078918,0.0001285431,0.0001550127,0.3920516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3976141,"threshold_uncertainty_score":0.9999325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07305037748895978,"score_gpt":0.3473099990619755,"score_spread":0.2742596215730157,"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."}}