{"id":"W4317618843","doi":"10.3390/su15031994","title":"A Bibliometric Analysis of Forest Gap Research during 1980–2021","year":2023,"lang":"en","type":"article","venue":"Sustainability","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intact forest landscape; China; Science Citation Index; Forest ecology; Forest management; Certified wood; Environmental resource management; Web of science; Geography; Forest inventory; Sustainable forest management; Citation; Forest dynamics; Ecology; Forestry; Environmental science; Political science; Library science; Ecosystem; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"not_applicable","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":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics","insufficient_payload"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.002488614,0.00009280176,0.0002017816,0.05208508,0.0001845543,0.00003616831,0.0003828013,0.00005054073,0.003449389],"category_scores_gemma":[0.001760026,0.00008601433,0.0001574787,0.4543632,0.000437751,0.0001818503,0.0008656767,0.0001379363,0.0006488402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006394098,"about_ca_system_score_gemma":0.00003567261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005417631,"about_ca_topic_score_gemma":0.0009002934,"domain_scores_codex":[0.9978675,0.000183869,0.0002498664,0.0003720708,0.0007282399,0.0005984068],"domain_scores_gemma":[0.9988374,0.0002318546,0.00005230506,0.0006613685,0.0001139304,0.0001031112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002021267,0.00006570051,0.9866396,0.0000993779,0.0000685919,0.00001420196,0.0003446179,0.005573018,0.00004995613,0.001317382,0.002209049,0.003598331],"study_design_scores_gemma":[0.0001127035,0.00003622641,0.9887643,0.000001560027,0.00005639129,8.19502e-8,0.0002349052,0.002710664,0.00004681028,0.004724524,0.003228965,0.00008283483],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855857,0.00001078374,0.000004233521,0.0005708038,0.00002367405,0.0003159071,0.000005970634,0.00004304061,0.01343983],"genre_scores_gemma":[0.984881,0.00002683367,0.00001778338,0.000005261132,0.00002078415,0.00003668014,0.00001363735,0.000008087138,0.01498993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4022781,"threshold_uncertainty_score":0.9974616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03995865179345331,"score_gpt":0.3626600476683026,"score_spread":0.3227013958748493,"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."}}