{"id":"W4210867846","doi":"10.1002/esp.5339","title":"Time‐lapse photogrammetry reveals hydrological controls of fine‐scale High‐Arctic glacier surface roughness evolution","year":2022,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Royal Geographical Society; Leverhulme Trust","keywords":"Geology; Glacier; Snow; Glacier mass balance; Surface roughness; Arctic; Elevation (ballistics); Climatology; Physical geography; Geomorphology; Atmospheric sciences; Geography; Oceanography; Geometry","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004471477,0.0001882429,0.0003872415,0.0000206065,0.0005525948,0.0000427866,0.0001784944,0.00006021811,0.004019357],"category_scores_gemma":[0.00009502174,0.0001338663,0.00006216668,0.0006774757,0.0001450873,0.0002002719,0.00006400907,0.0001956278,0.0000264003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006869396,"about_ca_system_score_gemma":0.0000677943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004951346,"about_ca_topic_score_gemma":0.002364629,"domain_scores_codex":[0.9985103,0.00006243957,0.0003361712,0.0003318041,0.0003724396,0.0003868435],"domain_scores_gemma":[0.9991338,0.0002831807,0.0001813523,0.0001679808,0.0001229122,0.0001107753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002171154,0.00007588273,0.9506004,0.0001531875,0.0000442068,0.000004451221,0.000371315,0.04683524,0.0001628516,0.0000184696,0.0002099525,0.001306869],"study_design_scores_gemma":[0.001267146,0.0007432537,0.9618261,0.00002566677,0.00005862186,0.00002072934,0.001250304,0.02483975,0.0001030025,0.001032526,0.008469398,0.0003634844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932712,0.005072457,0.0002607779,0.0003077928,0.0001447763,0.0003230114,0.0003491044,0.0000477575,0.0002230895],"genre_scores_gemma":[0.997587,0.000177665,0.0007569145,0.0001425594,0.00003750356,0.000005014378,0.00017319,0.000005979218,0.001114142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02199549,"threshold_uncertainty_score":0.9968911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009728039018552091,"score_gpt":0.2012184257860134,"score_spread":0.1914903867674613,"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."}}