{"id":"W2371692342","doi":"","title":"EQUIPMENT AND METHODS USED IN MARINE GEOLOGICAL SURVEY OF CANADA","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coring; Submarine pipeline; Bathymetry; Geological survey; Side-scan sonar; Underwater; Geology; Sonar; Seismic survey; Sampling (signal processing); Work (physics); Survey methodology; Survey research; Marine engineering; Oceanography; Remote sensing; Engineering; Seismology; Drilling","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":[0.002150428,0.001211737,0.00105771,0.01029956,0.003101206,0.001726497,0.002429697,0.0005906898,0.05126335],"category_scores_gemma":[0.008267367,0.0005794322,0.0006504243,0.0186306,0.0009000191,0.001120264,0.001486609,0.00144317,0.02082864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008509231,"about_ca_system_score_gemma":0.02926942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7302416,"about_ca_topic_score_gemma":0.8088387,"domain_scores_codex":[0.9949831,0.0003964209,0.0004314814,0.0006819283,0.003092919,0.0004141155],"domain_scores_gemma":[0.9886329,0.0003365857,0.0004944108,0.0008978112,0.009281917,0.0003564459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002327153,0.0001363986,0.03362345,0.001639816,0.00008221059,0.0006585999,0.001746701,0.005383231,0.007217628,0.03436795,0.4662026,0.4487089],"study_design_scores_gemma":[0.00003809202,0.00003483929,0.02864225,0.0003353439,0.00003600741,0.0002468788,0.0006495526,0.00103206,0.002416797,0.0022865,0.9642087,0.00007304052],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.02413967,0.006362403,0.195544,0.002541317,0.004633077,0.008154203,0.4063681,0.005398061,0.3468593],"genre_scores_gemma":[0.08188295,0.0102831,0.4179633,0.001906662,0.0004102593,0.01200354,0.2598757,0.001575868,0.2140987],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.2697584,"threshold_uncertainty_score":0.5426941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04568461345401222,"score_gpt":0.3532633033733933,"score_spread":0.3075786899193811,"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."}}