{"id":"W4210701693","doi":"10.2737/rds-2021-0003","title":"Field and spatial data for: Understanding the role of fire refugia in promoting ecosystem resilience of dry forests in the western United States","year":2021,"lang":"en","type":"dataset","venue":"Forest Service Research Data Archive","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service","funders":"Rocky Mountain Research Station","keywords":"Resilience (materials science); Psychological resilience; Resource (disambiguation); Environmental resource management; Field (mathematics); Agriculture; Geography; Ecosystem; Research data; Range (aeronautics); Environmental science; Ecology; Data science; Computer science; Engineering; Data curation; Archaeology","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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.007810514,0.0002858163,0.0005049359,0.0002768759,0.000228061,0.0001456649,0.007273205,0.0001655771,0.00001990311],"category_scores_gemma":[0.001778546,0.0001924078,0.00002913735,0.001261273,0.0002941272,0.0005666193,0.009306139,0.001073298,0.000007989636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705742,"about_ca_system_score_gemma":0.0001597341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1637787,"about_ca_topic_score_gemma":0.9033262,"domain_scores_codex":[0.9940991,0.00206071,0.0007723068,0.001058535,0.001267312,0.0007420658],"domain_scores_gemma":[0.986171,0.008642903,0.0003897643,0.004662269,0.00004135463,0.00009269387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001245296,0.0008803286,0.363805,0.01660819,0.0002076685,0.0002658081,0.0113183,0.002557075,0.0002149455,0.0001059623,0.5974519,0.005339547],"study_design_scores_gemma":[0.0009941784,0.0007689235,0.02900414,0.005343532,0.00005561259,0.00002339422,0.009267514,0.7772324,0.00004274144,0.002544908,0.1742684,0.000454268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1135413,0.0001881872,0.0001603507,0.0006026852,0.00005000679,0.002301124,0.8831338,0.000005065019,0.00001743114],"genre_scores_gemma":[0.2839218,0.0002411401,0.00007062531,0.00005224741,0.0000490828,0.0001029032,0.7155378,0.00002243784,0.000001925144],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7746753,"threshold_uncertainty_score":0.9987064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06311407981582394,"score_gpt":0.3354251757390965,"score_spread":0.2723110959232725,"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."}}