{"id":"W2737970866","doi":"10.22621/cfn.v131i1.1962","title":"Thematic Collection: Alvars in Canada","year":2017,"lang":"en","type":"article","venue":"The Canadian Field-Naturalist","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thematic map; Theme (computing); Naturalism; Geography; Library science; Club; Field (mathematics); History; Cartography; Biology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008775503,0.00195046,0.002004076,0.04662988,0.01532962,0.01623085,0.004642441,0.001254743,0.2098097],"category_scores_gemma":[0.02260538,0.0008696234,0.0009501188,0.07910195,0.003155174,0.005035917,0.006615405,0.002001005,0.06846701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06892364,"about_ca_system_score_gemma":0.2173551,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9189104,"about_ca_topic_score_gemma":0.9475606,"domain_scores_codex":[0.9896842,0.0005646845,0.00075523,0.0008530181,0.006588764,0.001554111],"domain_scores_gemma":[0.9242138,0.002645708,0.002082516,0.002542766,0.06119248,0.007322778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00001576756,0.000004412278,0.0002431011,0.0006241658,0.00000493805,0.00001470497,0.0005000402,0.00002708685,0.0001195041,0.002314528,0.9773775,0.0187543],"study_design_scores_gemma":[0.000001648582,0.000001264819,0.001031299,0.0003216018,0.000003854977,0.000008968964,0.000409804,0.000006455292,0.00003875692,0.0001359551,0.9980326,0.000007802253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.002147208,0.01725173,0.002467353,0.01189634,0.01592978,0.00161125,0.5558274,0.002294322,0.3905746],"genre_scores_gemma":[0.01774513,0.03762966,0.008510959,0.004011524,0.005452801,0.001936105,0.414159,0.006498815,0.504056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2098097,"threshold_uncertainty_score":0.7018835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132675865328571,"score_gpt":0.2191109849143537,"score_spread":0.207784226261068,"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."}}