{"id":"W4396540969","doi":"10.1016/j.gloenvcha.2024.102849","title":"An actor-centered, scalable land system typology for addressing biodiversity loss in the world’s tropical dry woodlands","year":2024,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Horizon 2020; European Research Council; Horizon 2020 Framework Programme; Humboldt-Universität zu Berlin; European Commission","keywords":"Woodland; Typology; Biodiversity; Geography; Land use; Environmental resource management; Land-use planning; Environmental planning; Agricultural biodiversity; Agroforestry; Ecology; Environmental science; Biology","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":[0.0001630302,0.0001595908,0.0001314574,0.00004390597,0.0002548183,0.00008683595,0.0003574232,0.00007514303,0.000437657],"category_scores_gemma":[0.00000165789,0.0001218865,0.00007631703,0.0001953239,0.0002333187,0.0002088648,0.000272049,0.00009426535,0.0003412778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007204624,"about_ca_system_score_gemma":0.000002916764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008021838,"about_ca_topic_score_gemma":0.001849933,"domain_scores_codex":[0.9987881,0.00008560784,0.0001331681,0.0003992628,0.0002584099,0.0003354635],"domain_scores_gemma":[0.9996433,0.00002592332,0.00003349478,0.0002148144,8.061157e-7,0.00008164083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005610428,0.0001260691,0.9959782,0.00004399802,0.00001463847,0.00005648273,0.0005870771,0.00001330055,0.00004398696,0.00004651023,0.0009635251,0.002070116],"study_design_scores_gemma":[0.000500735,0.00007864094,0.9348525,0.00002796632,0.00004199005,0.000009316179,0.001859873,0.001328358,0.000009648932,0.00001648685,0.06112251,0.0001519753],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955826,0.0001820794,0.00005539423,0.0009435109,0.0002852211,0.0005229701,0.0004344831,0.00005601447,0.001937746],"genre_scores_gemma":[0.9988682,0.00002590337,0.0001204227,0.0005903764,0.0001156094,0.00002935998,0.0001207896,0.000004657478,0.00012474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06112569,"threshold_uncertainty_score":0.4970388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04185751566023314,"score_gpt":0.2503637989966893,"score_spread":0.2085062833364561,"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."}}