{"id":"W2077580256","doi":"10.1016/j.coldregions.2014.04.004","title":"Comparing methods for estimating β points for use in statistical snow avalanche runout models","year":2014,"lang":"en","type":"article","venue":"Cold Regions Science and Technology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Parks Canada","keywords":"Snow; Digital elevation model; Range (aeronautics); Elevation (ballistics); Geology; Point (geometry); Geodesy; Meteorology; Geography; Remote sensing; Geomorphology; Geometry; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000905993,0.00008142022,0.0001849807,0.0001327342,0.0005333076,0.00006445396,0.000214567,0.00006061359,0.000004929259],"category_scores_gemma":[0.001820757,0.00006782457,0.00001476632,0.0006823279,0.000697946,0.0002208798,0.00003787583,0.00007785324,0.000001165666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008915703,"about_ca_system_score_gemma":0.00007662518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000215493,"about_ca_topic_score_gemma":0.001360055,"domain_scores_codex":[0.9990833,0.0000178121,0.0001693428,0.0003072401,0.00008102383,0.0003412114],"domain_scores_gemma":[0.9984361,0.001161468,0.0000529804,0.0001633588,0.0001308852,0.00005522331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002285219,0.0000351684,0.2120725,0.0000427106,0.000009447681,8.681313e-7,0.0002227555,0.006954402,0.000166648,0.552431,0.001503062,0.2265385],"study_design_scores_gemma":[0.000296224,0.00009490304,0.01440347,0.00002309922,0.000006318057,0.000003393177,0.000207953,0.9246912,0.00003738731,0.05493572,0.005210319,0.00008999876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04356455,0.00008497998,0.9538191,0.001477505,0.0001496383,0.0006726641,0.00001308133,0.00005410812,0.0001643668],"genre_scores_gemma":[0.3040658,0.00001005612,0.6957248,0.0001138182,0.00001701175,0.0000367512,0.000004657438,0.00000193928,0.00002513263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9177368,"threshold_uncertainty_score":0.4101825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09321407068035775,"score_gpt":0.3256886704342952,"score_spread":0.2324745997539374,"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."}}