{"id":"W4321996059","doi":"10.5194/egusphere-egu23-10395","title":"OBSPicker: A generalized transfer-learned OBS phase picker","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Seismometer; Seismology; Phase (matter); Submarine pipeline; Transfer (computing); Geology; Transfer of learning; Sequence (biology); Computer science; Set (abstract data type); False positive paradox; Tectonics; Data set; Algorithm; Artificial intelligence; Physics; Chemistry","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":[0.0007101477,0.001172793,0.0006589869,0.0007467605,0.0003089684,0.0005015896,0.002720623,0.001106668,0.003983695],"category_scores_gemma":[0.00156032,0.0004685035,0.0007710331,0.0005951569,0.0004474835,0.001421268,0.001701472,0.001473314,0.001680107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006274742,"about_ca_system_score_gemma":0.001062828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006568044,"about_ca_topic_score_gemma":0.01008911,"domain_scores_codex":[0.9996961,0.00002993559,0.0000164283,0.000126906,0.0000758021,0.00005479898],"domain_scores_gemma":[0.9996207,0.00008124299,0.00004108331,0.00009652925,0.0001239284,0.00003648895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004473504,0.0004576285,0.00850035,0.0001571465,0.0001526762,0.0003243893,0.00008731544,0.2377052,0.01622668,0.002792755,0.02142025,0.7117283],"study_design_scores_gemma":[0.00002886153,0.00009588743,0.001056058,0.00000673005,0.00001309458,0.00005755559,0.00001305442,0.988988,0.006088426,0.00139222,0.002241815,0.00001835238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1540375,0.0006515127,0.797046,0.0004073745,0.0002804984,0.0004366995,0.003587555,0.03830756,0.005245229],"genre_scores_gemma":[0.5640436,0.0002607807,0.4051531,0.0007577552,0.00008993641,0.0005359734,0.01127486,0.0008485529,0.01703541],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006568044,"threshold_uncertainty_score":0.01332682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1115427132205292,"score_gpt":0.3358366934353971,"score_spread":0.2242939802148679,"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."}}