{"id":"W2128405974","doi":"10.1139/e09-068","title":"A flowline map of glaciated Canada based on remote sensing dataThis paper is accompanied by a large foldout map entitled <i>A flowline map of glaciated Canada based on remote sensing</i> <i>data</i> (see pocket on back cover).","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Earth Sciences","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Geological Survey of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geology; Drumlin; Landform; Glacial landform; Moraine; Ice sheet; Terrain; Remote sensing; Glacier; Glaciology; Geomorphology; Shuttle Radar Topography Mission; Ice stream; Cryosphere; Paleontology; Digital elevation model; Oceanography; Cartography; Sea ice; Stratigraphy; Geography","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":[0.00008130203,0.0007771819,0.0002039086,0.005539963,0.001188124,0.00118019,0.0004258361,0.0002093243,0.02850855],"category_scores_gemma":[0.0003039061,0.0001420589,0.0002296037,0.008200578,0.0002502018,0.0002825777,0.0003557825,0.0003554244,0.003399013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008046403,"about_ca_system_score_gemma":0.02517701,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9779077,"about_ca_topic_score_gemma":0.9834593,"domain_scores_codex":[0.9998984,0.000002695313,0.00000396529,0.00001530606,0.00004917446,0.00003037814],"domain_scores_gemma":[0.9996277,0.00001018727,0.00002312892,0.000007085389,0.0002829347,0.00004903763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001950551,0.00009407452,0.04275976,0.001492153,0.00007293758,0.0005857869,0.001392721,0.004915521,0.01371344,0.005901033,0.5958474,0.3330301],"study_design_scores_gemma":[0.00004991643,0.00003282828,0.2761548,0.0006087446,0.00004721146,0.0002528871,0.001281742,0.00402399,0.002161227,0.0006131753,0.7147009,0.00007261925],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1155761,0.006176035,0.009562492,0.001236999,0.0004441987,0.0009271078,0.6957887,0.004961008,0.1653273],"genre_scores_gemma":[0.2821279,0.01275448,0.05389131,0.0006296763,0.000151867,0.0005211885,0.5109878,0.0008749671,0.1380609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02850855,"threshold_uncertainty_score":0.09537059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01746526616988905,"score_gpt":0.2273162172240024,"score_spread":0.2098509510541134,"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."}}