{"id":"W4398888204","doi":"10.7910/dvn/ubrdcl/dwjm0d","title":"TDF_vector_map.shx","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Replication (statistics); Resilience (materials science); Diversity (politics); Geography; Psychological resilience; Dry forest; Tropical and subtropical dry broadleaf forests; Ecology; Environmental resource management; Forestry; Environmental science; Biology; Psychology; Political science; Social psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001204792,0.003299622,0.001884388,0.004900611,0.0009805588,0.003583722,0.004764592,0.002834788,0.2557366],"category_scores_gemma":[0.007971507,0.001176998,0.001549856,0.00950916,0.0006641393,0.002993851,0.002996062,0.002254729,0.2491402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001982989,"about_ca_system_score_gemma":0.002405264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02908757,"about_ca_topic_score_gemma":0.03413627,"domain_scores_codex":[0.9988995,0.0001808504,0.0001264552,0.0003266346,0.0002505888,0.0002160054],"domain_scores_gemma":[0.9977012,0.0006796188,0.0001850635,0.0006666632,0.0005231939,0.0002442083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002696683,0.000009378268,0.0002102968,0.0004018814,0.00001961794,0.000008041006,0.00001615446,0.0001762609,0.00005130888,0.0005170531,0.9973872,0.001175853],"study_design_scores_gemma":[0.0001864666,0.000009642933,0.001006934,0.000227602,0.00002201363,0.00002644202,0.00005442392,0.000431658,0.0003756488,0.002368371,0.9952571,0.00003370726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003055816,0.00002607887,0.00006531825,0.00004469147,0.00001706041,0.000005051494,0.9983574,0.0009083122,0.0005455208],"genre_scores_gemma":[0.0002969044,0.00005483351,0.000310824,0.00004714761,0.000007519197,0.00006204356,0.9981514,0.0004487594,0.0006206048],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7442634,"threshold_uncertainty_score":0.8555243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711334981960955,"score_gpt":0.2081957583262285,"score_spread":0.191082408506619,"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."}}