{"id":"W1560634373","doi":"10.1002/esp.3532","title":"Size, shape and spatial arrangement of mega‐scale glacial lineations from a large and diverse dataset","year":2014,"lang":"en","type":"article","venue":"Earth Surface Processes and Landforms","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":183,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Environment Research Council; Sight Research UK","keywords":"Lineation; Geology; Landform; Fluvial; Glacial period; Mode (computer interface); STREAMS; Geomorphology; Seabed gouging by ice; Scale (ratio); Physical geography; Arctic ice pack; Geodesy; Paleontology; Climatology; Antarctic sea ice; Sea ice; Tectonics; Cartography; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000574174,0.0002293711,0.0003329098,0.003169198,0.0003730854,0.0006919562,0.0003820833,0.0002820655,0.001856456],"category_scores_gemma":[0.001652492,0.0001057161,0.0003337195,0.004022495,0.0002664309,0.0003384092,0.000777489,0.0002241512,0.0009653465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003151847,"about_ca_system_score_gemma":0.0004036931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140551,"about_ca_topic_score_gemma":0.03550583,"domain_scores_codex":[0.9994825,0.00008400751,0.00006409602,0.0001922104,0.00008647341,0.00009068326],"domain_scores_gemma":[0.9988287,0.0003271736,0.0003183717,0.0002022961,0.0002253193,0.00009811548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009979444,0.0000171907,0.9787127,0.0001135046,0.0001184355,0.0001307336,0.0003585602,0.0009378098,0.002079353,0.0001301274,0.004408171,0.01289366],"study_design_scores_gemma":[0.000007026765,0.00001525584,0.9927609,0.00002284992,0.00002859093,0.0001263126,0.0006806316,0.001532309,0.0003906902,0.00006432291,0.004361643,0.000009505879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650069,0.0002063733,0.0005417161,0.00002849558,0.000006680554,0.00001218554,0.03327758,0.00007724185,0.0008428653],"genre_scores_gemma":[0.919537,0.000146291,0.002457455,0.00001466506,0.000007513001,0.00007865635,0.07726841,0.00004305124,0.0004468491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01140551,"threshold_uncertainty_score":0.0226782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117529897253717,"score_gpt":0.2100662781669388,"score_spread":0.1983132884415671,"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."}}