{"id":"W6925467142","doi":"10.17632/kgbsjvrj32.1","title":"Distribution and morphometry of pingos, western Canadian Arctic, Northwest Territories, Canada: Datasets and Supplementary Materials","year":2023,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Rabies epidemiology and control","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distribution (mathematics); Arctic; Spatial distribution; Geographic information system; The arctic; Spatial analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.001037035,0.001466571,0.001062846,0.00646443,0.002568302,0.00205645,0.003041031,0.0008181343,0.03569303],"category_scores_gemma":[0.004804864,0.0007911127,0.00102906,0.01867904,0.000632431,0.0006117541,0.001603949,0.001058921,0.01269266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01664317,"about_ca_system_score_gemma":0.04609931,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9885936,"about_ca_topic_score_gemma":0.9934419,"domain_scores_codex":[0.9990019,0.00004719544,0.00008752391,0.0001833059,0.0003758199,0.0003042232],"domain_scores_gemma":[0.9950954,0.0002981873,0.0003105744,0.0004459148,0.003353487,0.0004965299],"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":[0.00005674861,0.00002187706,0.01700439,0.0005792096,0.00007540725,0.00005380475,0.0001946403,0.0009020458,0.0001647544,0.000832895,0.9744141,0.005700132],"study_design_scores_gemma":[0.0001221044,0.00001276201,0.1714917,0.0008348589,0.0001078868,0.0001341325,0.001153326,0.00119355,0.0006410933,0.001142914,0.8230393,0.0001264532],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006282,0.00004387657,0.00007746754,0.00003067328,0.00000810951,0.00001531319,0.9983706,0.00007189586,0.0007539326],"genre_scores_gemma":[0.003466762,0.0001619398,0.0009581288,0.00004514049,0.000005588385,0.000148679,0.9932706,0.00006940641,0.00187368],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03569303,"threshold_uncertainty_score":0.1207553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01035040097339963,"score_gpt":0.228774022710446,"score_spread":0.2184236217370463,"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."}}