{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.006309881,0.0004994062,0.00102972,0.1140032,0.0008573405,0.003534828,0.0006358672,0.0007215332,0.003003963],"category_scores_gemma":[0.02540659,0.0001601843,0.001424347,0.1597011,0.0004774678,0.003736895,0.001493589,0.000443757,0.0009078732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00352905,"about_ca_system_score_gemma":0.004831393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01266789,"about_ca_topic_score_gemma":0.01239209,"domain_scores_codex":[0.9917827,0.001099409,0.002092566,0.0006439785,0.003854282,0.0005270973],"domain_scores_gemma":[0.9693001,0.01094014,0.008124886,0.0006230368,0.01021706,0.0007948262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003040726,0.0001624621,0.780935,0.009764331,0.0008137105,0.0006723601,0.00268186,0.002027859,0.0008547985,0.00332633,0.0264529,0.1720044],"study_design_scores_gemma":[0.00001401248,0.00009548417,0.958868,0.001158636,0.0004484094,0.0006018963,0.003901743,0.002157186,0.0004842796,0.0007363672,0.03148712,0.00004697814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7424774,0.05222491,0.00246609,0.003317261,0.0003768572,0.0006274748,0.1627041,0.0003915699,0.03541438],"genre_scores_gemma":[0.9018283,0.02100766,0.003437885,0.0002318136,0.0004697358,0.0007582355,0.07025989,0.00004992804,0.001956576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8859968,"threshold_uncertainty_score":0.03337026,"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."}}