{"id":"W2886799279","doi":"10.1002/ecs2.2367","title":"Better late than never: a synthesis of strategic land retirement and restoration in California","year":2018,"lang":"en","type":"article","venue":"Ecosphere","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Endangered species; Habitat; Restoration ecology; San Joaquin; Critical habitat; Habitat conservation; Context (archaeology); Vegetation (pathology); Environmental resource management; Agriculture; Ecology; Geography; Environmental planning; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001284518,0.00005855681,0.00007539063,0.000007539366,0.00003125231,0.00001256026,0.00005517951,0.00002580668,0.001567783],"category_scores_gemma":[0.000004416656,0.00004726116,0.00001170573,0.00006725737,0.00005811682,0.00007833854,0.00004924747,0.00002882798,0.0002946717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002970942,"about_ca_system_score_gemma":0.000002193211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000736407,"about_ca_topic_score_gemma":0.003436215,"domain_scores_codex":[0.9995426,0.0000255882,0.0001134087,0.0001154056,0.0001010458,0.0001019374],"domain_scores_gemma":[0.9998182,0.00001059866,0.00004065914,0.0001013176,0.000002152071,0.00002704946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003545539,0.0000607592,0.9728138,0.00002637604,0.00001010409,0.000006296612,0.0002754685,0.0001329663,0.0006555278,0.00005404666,0.01432115,0.01160798],"study_design_scores_gemma":[0.000307212,0.0001043593,0.9821918,0.00005276064,0.00001180655,4.877987e-7,0.0001180234,0.00208619,0.0008399129,0.001338559,0.01281826,0.000130609],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9533128,0.00001646464,0.00001035639,0.0005249471,0.00002579766,0.00008612303,0.000005396449,0.000006658121,0.04601151],"genre_scores_gemma":[0.9991428,0.0000228131,0.000243222,0.0001407945,0.00002879531,0.000007154822,0.000001550553,0.000004470876,0.0004084177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04583004,"threshold_uncertainty_score":0.9993449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465317794027607,"score_gpt":0.2099415028851803,"score_spread":0.1952883249449043,"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."}}