{"id":"W2331408305","doi":"10.1071/aseg2001ab097","title":"A heuristic method of removing micro-pulsations from airborne magnetic data","year":2001,"lang":"en","type":"article","venue":"ASEG Extended Abstracts","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Data processing; Amplitude; Environmental science; Nova scotia; Heuristic; Data quality; Meteorology; Noise (video); Geology; Computer science; Geography; Engineering; Physics; Database; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004562889,0.0001641626,0.0002842563,0.00007546982,0.00009709186,0.00003864579,0.0005490248,0.0000824196,0.002358599],"category_scores_gemma":[0.000729904,0.0001372688,0.00006175609,0.0004427876,0.00006381299,0.0002125621,0.00004231327,0.0002349552,0.0003532395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002860284,"about_ca_system_score_gemma":0.00005921981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008998989,"about_ca_topic_score_gemma":0.0007904296,"domain_scores_codex":[0.99828,0.0001915916,0.0004129095,0.0004707687,0.0002801493,0.0003646213],"domain_scores_gemma":[0.9975177,0.001386876,0.0001599188,0.0006781393,0.00005555769,0.0002018123],"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":[0.00003695092,0.00008075317,0.0007621999,0.00000900413,0.00001644434,0.00005436012,0.00002650982,0.000455762,0.0006951068,0.00003262991,0.0002897797,0.9975405],"study_design_scores_gemma":[0.0002233076,0.0001282157,0.9639442,0.00001937313,0.00005849375,0.00002975214,0.00002660964,0.008456785,0.0009358056,0.02202522,0.003981222,0.0001710431],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630041,0.002585284,0.01663392,0.001390657,0.0005608573,0.0004126797,0.001496054,0.0001367762,0.01377973],"genre_scores_gemma":[0.8339956,0.00006276838,0.1646661,0.0001896254,0.0001647145,6.210817e-7,0.0005909039,0.000004808093,0.0003248109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9973695,"threshold_uncertainty_score":0.9985534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03566626526339672,"score_gpt":0.2914701210247831,"score_spread":0.2558038557613864,"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."}}