{"id":"W4296641359","doi":"10.3390/f13101549","title":"Forestry Big Data: A Review and Bibliometric Analysis","year":2022,"lang":"en","type":"review","venue":"Forests","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; Asia-Pacific Network for Sustainable Forest Management and Rehabilitation","keywords":"Big data; Computer science; Data science; Forestry; Web of science; Field (mathematics); Data processing; Database; Data mining; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005154698,0.001414144,0.003299597,0.05301103,0.0010324,0.003553782,0.001833456,0.001330132,0.007038139],"category_scores_gemma":[0.01587466,0.0007327129,0.002572122,0.06240233,0.0008918921,0.004173848,0.001762599,0.001129704,0.001343777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002194268,"about_ca_system_score_gemma":0.00895366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005878368,"about_ca_topic_score_gemma":0.01161967,"domain_scores_codex":[0.9964557,0.0006812661,0.0009446014,0.0003198449,0.00144322,0.0001554422],"domain_scores_gemma":[0.9796135,0.0141264,0.002313161,0.0004248803,0.003183076,0.0003389208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008260384,0.00007663672,0.002833253,0.2609828,0.001174559,0.0001930522,0.0004273955,0.0005687893,0.0003225534,0.004509277,0.03812326,0.6907058],"study_design_scores_gemma":[0.00004319413,0.0001260494,0.01812005,0.1958459,0.005249644,0.001029939,0.0009127281,0.0006137657,0.00060024,0.005995015,0.7713041,0.0001593329],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000563286,0.9943662,0.0004545531,0.0012073,0.0002505225,0.00005824591,0.0008883431,0.00003421013,0.002177384],"genre_scores_gemma":[0.002600439,0.9956248,0.000590204,0.0002501511,0.0001989259,0.00005887517,0.0005056746,0.000006670231,0.0001642209],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9469889,"threshold_uncertainty_score":0.02726096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1205424181742747,"score_gpt":0.356727223184501,"score_spread":0.2361848050102263,"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."}}