{"id":"W2927483575","doi":"10.1002/ppp.1997","title":"Application of distributed temperature sensing for mountain permafrost mapping","year":2019,"lang":"en","type":"article","venue":"Permafrost and Periglacial Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"BGC Engineering (Canada); University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Permafrost; Geothermal gradient; Geology; Snow; Rock glacier; Remote sensing; Glacier; Spatial distribution; Spatial variability; Geomorphology; Hydrology (agriculture); Environmental science; Soil science; Geotechnical engineering; Geophysics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00009850648,0.0001351211,0.0002162105,0.00002397643,0.0002903226,0.00006315795,0.00007952541,0.00006931979,0.0001705523],"category_scores_gemma":[0.00007044056,0.000113542,0.0000377473,0.0003053758,0.00007822675,0.0001722042,0.0000127272,0.00006760765,0.000009704291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003994103,"about_ca_system_score_gemma":0.00006030638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003806535,"about_ca_topic_score_gemma":0.001098201,"domain_scores_codex":[0.9992107,0.00001086872,0.0002069529,0.0002427544,0.0001250964,0.0002036227],"domain_scores_gemma":[0.9994065,0.0001398588,0.00009514389,0.0001015537,0.000205093,0.00005187359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000680399,0.0000109551,0.986436,0.0005101248,0.00001786093,2.832541e-7,0.001328295,0.0003166594,0.004023736,0.00007114802,0.0001763904,0.007040524],"study_design_scores_gemma":[0.0004560346,0.000086937,0.9280556,0.00004361408,0.00002375823,0.000006573191,0.003388831,0.01321024,0.0004278303,0.0002831986,0.05376105,0.0002562779],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903088,0.001663714,0.00161647,0.0003388315,0.0001666809,0.0004955095,0.005130965,0.00003124944,0.0002478441],"genre_scores_gemma":[0.9959357,0.0001704638,0.0005545988,0.0001436803,0.0001859335,0.000004417313,0.002902296,0.000005265383,0.00009763215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05838034,"threshold_uncertainty_score":0.463011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093214608401295,"score_gpt":0.2189838489578645,"score_spread":0.2080517028738516,"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."}}