{"id":"W2471201622","doi":"10.1139/cjes-2016-0034","title":"Modelling the spatial distribution of permafrost in Labrador–Ungava using the temperature at the top of permafrost","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Earth Sciences","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Memorial University of Newfoundland; Parks Canada; Association of Canadian Universities for Northern Studies; University of Ottawa","keywords":"Permafrost; Subarctic climate; Geology; Snow; Land cover; Spatial distribution; Physical geography; Snow cover; Climatology; Geomorphology; Land use; Remote sensing; Geography; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001408556,0.0003080962,0.0002304826,0.0005671654,0.0003676641,0.0008955123,0.0008509119,0.0003994211,0.001652732],"category_scores_gemma":[0.0004806233,0.0002497716,0.0005520075,0.0007593481,0.0003868162,0.0003244872,0.0003592996,0.0002698929,0.000217759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003991613,"about_ca_system_score_gemma":0.002013703,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7993287,"about_ca_topic_score_gemma":0.823068,"domain_scores_codex":[0.9998866,0.00001738347,0.000005345959,0.00003811793,0.00001251326,0.00003996406],"domain_scores_gemma":[0.9998407,0.00003970807,0.0000352463,0.0000187529,0.00004196849,0.00002357313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001043597,0.0000435168,0.1180776,0.00004104159,0.0001264213,0.0001386633,0.0001039773,0.8704928,0.002117377,0.000489948,0.0008094758,0.007454838],"study_design_scores_gemma":[0.00004063874,0.00001512292,0.08978477,0.00002313652,0.00003229065,0.00002790427,0.0001931885,0.9074345,0.0006062774,0.00020505,0.001609578,0.00002763994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915119,0.000177144,0.002319068,0.00009645521,0.000008311941,0.00001565505,0.002863421,0.0001798151,0.002828241],"genre_scores_gemma":[0.9960204,0.00005636468,0.002067124,0.00001202645,0.000002772068,0.00001563617,0.001263051,0.00001862045,0.0005440547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2006713,"threshold_uncertainty_score":0.4037061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04123899046393023,"score_gpt":0.2338053259004788,"score_spread":0.1925663354365485,"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."}}