{"id":"W4388709601","doi":"10.14214/sf.23034","title":"Increasing access to forest data for enhancing forest benefits to all","year":2023,"lang":"en","type":"article","venue":"Silva Fennica","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Strategic Research Council","keywords":"Business; Forest ecology; Ecoforestry; Forest management; Forest restoration; Forest inventory; Transparency (behavior); Certified wood; Forest protection; Forest farming; Corporate governance; Environmental resource management; Community forestry; Intact forest landscape; Natural resource economics; Agroforestry; Forestry; Geography; Ecosystem; Ecology; Environmental science; Economics; Political science; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005241818,0.000147909,0.0002093408,0.00003324632,0.0005640658,0.000110444,0.001219598,0.00009868812,0.0000491201],"category_scores_gemma":[0.000759752,0.00006592936,0.00006228636,0.0005672774,0.00003784146,0.0002401377,0.0020186,0.00007038095,0.0004927767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002535555,"about_ca_system_score_gemma":0.000009226931,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006792623,"about_ca_topic_score_gemma":0.1031666,"domain_scores_codex":[0.998594,0.00003176544,0.0001805041,0.0005262537,0.0001384763,0.0005290239],"domain_scores_gemma":[0.9988503,0.000667983,0.00004779944,0.0001786213,0.00007455868,0.0001806851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000445461,0.0001135716,0.6530536,0.00003648981,0.0001184967,0.00001624689,0.0002843315,0.00045254,0.01082589,0.0006817016,0.3072984,0.02667334],"study_design_scores_gemma":[0.0001141358,0.0002893649,0.8444507,0.00002722304,0.00002362675,0.000002224756,0.0002239947,0.00008392715,0.0001777982,0.0002940556,0.1541102,0.0002028056],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806538,0.00004296576,0.000008326675,0.01734153,0.0002780751,0.0006222162,0.0006143847,0.0001626394,0.0002760265],"genre_scores_gemma":[0.9952392,0.0000365243,0.0003308852,0.003088486,0.0003152333,0.00004877409,0.0006685487,0.000001481585,0.0002708474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1913971,"threshold_uncertainty_score":0.9131983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1282169331176763,"score_gpt":0.3060651086274008,"score_spread":0.1778481755097245,"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."}}