{"id":"W4384698425","doi":"10.1080/08941920.2023.2230453","title":"<i>Seeing the Forest for the Trees</i> Sequel I: An Extension of the 1985–2017 Bibliometric Analysis of Environmental and Resource Sociology","year":2023,"lang":"en","type":"article","venue":"Society & Natural Resources","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sociology; Resource (disambiguation); Natural resource; Environmental sociology; Social science; Extension (predicate logic); Bibliometrics; Environmental studies; Natural resource management; Regional science; Library science; Political science; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01265947,0.0003693783,0.0004429268,0.01666899,0.004640132,0.006072699,0.0009540488,0.001004653,0.01149976],"category_scores_gemma":[0.08184814,0.0002241476,0.0007577001,0.04380466,0.003005277,0.006648169,0.004553956,0.002397563,0.002940065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004757516,"about_ca_system_score_gemma":0.006994665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02435084,"about_ca_topic_score_gemma":0.04228928,"domain_scores_codex":[0.9913812,0.002710598,0.001294248,0.0006824916,0.003390766,0.000540675],"domain_scores_gemma":[0.924587,0.02857093,0.01104351,0.006318654,0.02766515,0.001814741],"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":[0.00008881235,0.0000405705,0.02243732,0.001180625,0.00005499469,0.000423702,0.03401465,0.0001321799,0.001761568,0.02703753,0.8570809,0.05574717],"study_design_scores_gemma":[0.000008319881,0.00003634176,0.06751987,0.001647948,0.00004312502,0.0003862608,0.03258437,0.0004436952,0.001913507,0.006689843,0.8886398,0.00008681222],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.195511,0.01494533,0.04157068,0.4153516,0.07952929,0.001744497,0.05484794,0.001540162,0.1949596],"genre_scores_gemma":[0.6837392,0.01805057,0.04283167,0.06330662,0.05460455,0.003707524,0.04198559,0.003501392,0.08827288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.983331,"threshold_uncertainty_score":0.0669505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0189178332906442,"score_gpt":0.2648230821774819,"score_spread":0.2459052488868377,"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."}}