{"id":"W3166646198","doi":"10.3390/f12060727","title":"The United States’ Implementation of the Montréal Process Indicator of Forest Fragmentation","year":2021,"lang":"en","type":"article","venue":"Forests","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fragmentation (computing); Sustainability; Environmental resource management; Geography; Agriculture; Shrub; Land cover; Forest cover; Indicator value; Land use; Environmental planning; Environmental science; Ecology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001320863,0.00006635639,0.00006203864,0.00002438529,0.0001317051,0.00001450664,0.0002226397,0.0000207776,0.0005356407],"category_scores_gemma":[0.00002048597,0.00004012638,0.00004153388,0.0004541627,0.0001552288,0.00009218855,0.0001360433,0.0000452082,0.0000438808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000343547,"about_ca_system_score_gemma":0.00001875443,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003458991,"about_ca_topic_score_gemma":0.0309007,"domain_scores_codex":[0.9991905,0.00004615516,0.0002136878,0.0001018452,0.0003048221,0.0001429603],"domain_scores_gemma":[0.9995055,0.00004174324,0.0001962404,0.0002152597,0.00001608513,0.00002521633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001140004,0.00002874024,0.9816514,0.00001951747,0.0000164581,6.039187e-7,0.001289874,0.006306421,0.0001026524,0.001505228,0.00704147,0.002026238],"study_design_scores_gemma":[0.0003137127,0.00003553431,0.9815979,0.000008217829,0.00001922019,6.722454e-7,0.000737773,0.001324619,0.004964996,0.002514717,0.008431389,0.00005124174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981287,0.00002673656,0.00003220744,0.0006676757,0.00006590627,0.0002299781,0.00001512138,0.000006785306,0.0008268805],"genre_scores_gemma":[0.9991887,0.00003736219,0.00003278902,0.0001112077,0.00001317505,0.00002234139,0.00007204606,0.000007013864,0.0005153585],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0274417,"threshold_uncertainty_score":0.9867828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006449024888863152,"score_gpt":0.2649366224585695,"score_spread":0.2584875975697064,"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."}}