{"id":"W2520459778","doi":"","title":"The output of predictive deconvolution’","year":2015,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geoscience BC","funders":"","keywords":"Deconvolution; Autoregressive model; Wavelet; Seismic vibrator; Reflection (computer programming); Mean squared prediction error; Series (stratigraphy); Operator (biology); Algorithm; Mathematics; Blind deconvolution; Linear prediction; Applied mathematics; Phase (matter); Computer science; Econometrics; Artificial intelligence; Geology; Physics; Acoustics","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":[0.001251699,0.0006794154,0.0005566401,0.0007671915,0.0004549467,0.001750919,0.0007702683,0.0008995741,0.01138026],"category_scores_gemma":[0.003911965,0.000342578,0.0005399827,0.0008099778,0.001034601,0.001774792,0.001297956,0.001029621,0.004589923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004891689,"about_ca_system_score_gemma":0.0007702788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101066,"about_ca_topic_score_gemma":0.0005063559,"domain_scores_codex":[0.9991999,0.0001069481,0.00003461365,0.0002286458,0.0003263959,0.0001034159],"domain_scores_gemma":[0.9989957,0.0002548452,0.00009492909,0.0002740679,0.0003433767,0.00003713703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006239164,0.0001152846,0.005387709,0.0005016135,0.00009766388,0.0007254027,0.0007796531,0.0412613,0.1180828,0.1559059,0.010113,0.6664058],"study_design_scores_gemma":[0.00003286912,0.0001858451,0.01007663,0.00009580106,0.00006073728,0.001291791,0.0003415786,0.5828384,0.2583912,0.08652694,0.06002859,0.0001297534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.05057542,0.0001988345,0.9243385,0.0004236025,0.000358,0.00004045813,0.0005769277,0.001435722,0.02205261],"genre_scores_gemma":[0.6600168,0.0003726292,0.3021497,0.000232173,0.000143513,0.00008751834,0.001135256,0.0008684453,0.03499394],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01138026,"threshold_uncertainty_score":0.03807074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06540185688721796,"score_gpt":0.2460934691067102,"score_spread":0.1806916122194922,"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."}}