{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000194358,0.0002404844,0.0001409691,0.000612282,0.0001653334,0.0002877555,0.0003253332,0.0001730898,0.000600349],"category_scores_gemma":[0.0002973858,0.00009440192,0.0001614808,0.0006310236,0.0001183907,0.0002579966,0.0002429774,0.0001380121,0.00007087009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003298595,"about_ca_system_score_gemma":0.0002235502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005770379,"about_ca_topic_score_gemma":0.009461344,"domain_scores_codex":[0.9999148,0.00001703073,0.000003492632,0.00003655218,0.00002081826,0.000007283596],"domain_scores_gemma":[0.9998728,0.00003667516,0.00002235004,0.00001856789,0.00003731045,0.00001225892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004157982,0.0002534442,0.1758219,0.0003096862,0.000188912,0.0002746089,0.0003673152,0.2079219,0.2092348,0.001585887,0.001554905,0.4020709],"study_design_scores_gemma":[0.00007425413,0.0001305923,0.179296,0.00004004018,0.00006493574,0.0001911697,0.0002526778,0.7900401,0.02383209,0.00233864,0.003696078,0.00004352899],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9079431,0.0005505685,0.08415768,0.0001609473,0.00004770745,0.00004871195,0.001031244,0.0006296762,0.005430253],"genre_scores_gemma":[0.979133,0.00005728496,0.02047016,0.0000134394,0.00001116269,0.000009530271,0.0001378249,0.000006051053,0.0001615119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005770379,"threshold_uncertainty_score":0.0114736,"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."}}