{"id":"W2317789844","doi":"10.1190/1.3255408","title":"Validating land data quality of simultaneous multiple vibrator acquisition","year":2009,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"ConocoPhillips (Canada)","funders":"","keywords":"Computer science; Vibrator (electronic); Quality (philosophy); Data quality; Data acquisition; Seismic vibrator; Remote sensing; Acoustics; Engineering; Geology; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003630256,0.0004892488,0.0006034355,0.0009950261,0.000774023,0.001166855,0.001168521,0.0009536427,0.003003075],"category_scores_gemma":[0.01045565,0.0003790317,0.0004607021,0.001496902,0.0007784268,0.001644747,0.001261964,0.0006068667,0.000785767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004953168,"about_ca_system_score_gemma":0.0006193317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007208682,"about_ca_topic_score_gemma":0.01297902,"domain_scores_codex":[0.9974717,0.0004463443,0.0001409526,0.0006707605,0.001027037,0.0002433436],"domain_scores_gemma":[0.9930066,0.002353596,0.0003689222,0.001092028,0.003019791,0.0001590428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002679513,0.0005507374,0.1411071,0.0006691676,0.0004702046,0.001070596,0.002488326,0.05990043,0.4590444,0.00206489,0.005069938,0.3248848],"study_design_scores_gemma":[0.0003866721,0.0007969103,0.3765282,0.0001253122,0.0002535149,0.0008861135,0.001852876,0.2938849,0.3064065,0.002395576,0.01628399,0.0001993409],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8526313,0.0001962413,0.1374777,0.0002995628,0.0001084958,0.0001696617,0.003089227,0.0019492,0.004078778],"genre_scores_gemma":[0.894325,0.00006941441,0.1007718,0.0000974736,0.00002817676,0.0001371537,0.002943534,0.0004526142,0.00117498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007208682,"threshold_uncertainty_score":0.01919883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03595123829432569,"score_gpt":0.2963947447652637,"score_spread":0.260443506470938,"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."}}