{"id":"W2067363266","doi":"10.1190/tle32050524.1","title":"High Arctic marine geophysical data acquisition","year":2013,"lang":"en","type":"article","venue":"The Leading Edge","topic":"Geological Studies and Exploration","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of National Defence; Geological Survey of Canada","funders":"","keywords":"Bathymetry; Geology; Arctic; Reflection (computer programming); The arctic; Oceanography; Data acquisition; Sonar; Joint (building); Seismology; Remote sensing; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001580662,0.0006089322,0.00059103,0.002802916,0.001335111,0.001384248,0.0009643845,0.0004510683,0.009960094],"category_scores_gemma":[0.001972415,0.000232933,0.0003584054,0.004072995,0.0002387954,0.0006464632,0.001707062,0.0007532936,0.007976391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007531957,"about_ca_system_score_gemma":0.003544472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04970528,"about_ca_topic_score_gemma":0.0703308,"domain_scores_codex":[0.9989194,0.0001203144,0.00008191082,0.0001916578,0.0005542641,0.0001324359],"domain_scores_gemma":[0.9974958,0.00009713121,0.00009700633,0.0003161072,0.001820533,0.0001733653],"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":[0.0005678304,0.000394983,0.1254274,0.0007140695,0.0001605648,0.001277324,0.001614022,0.009869634,0.03214527,0.007227947,0.3464012,0.4741997],"study_design_scores_gemma":[0.0001240461,0.0001525127,0.1753127,0.0003510658,0.00009855781,0.0004863758,0.0009855392,0.01358334,0.01595156,0.003008816,0.7898143,0.0001311728],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1324332,0.001650831,0.08064984,0.001325365,0.0008840991,0.002049987,0.4553729,0.009503499,0.3161303],"genre_scores_gemma":[0.2685489,0.001922378,0.1693762,0.001157143,0.0007357171,0.001865871,0.5115908,0.001670738,0.04313225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04970528,"threshold_uncertainty_score":0.09883189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04137811758326317,"score_gpt":0.2230422954843538,"score_spread":0.1816641779010906,"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."}}