{"id":"W4200497842","doi":"10.1002/essoar.10509050.1","title":"Pair Selection Optimization for InSAR Time Series Processing","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Geodynamics; Computer science; Interferometric synthetic aperture radar; Series (stratigraphy); World Wide Web; Library science; Geology; Artificial intelligence; Synthetic aperture radar; Seismology","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":[0.001398474,0.001970774,0.001254891,0.001400973,0.0006089375,0.001019887,0.001211081,0.001145943,0.007584868],"category_scores_gemma":[0.003950709,0.0006595706,0.001195699,0.001665067,0.0006096669,0.00101148,0.001306886,0.001246817,0.001965631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005214921,"about_ca_system_score_gemma":0.0009091694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002491043,"about_ca_topic_score_gemma":0.002465875,"domain_scores_codex":[0.9987722,0.0005820785,0.00004982232,0.0002300395,0.000258858,0.0001070745],"domain_scores_gemma":[0.9985021,0.00104477,0.00008160789,0.0001074621,0.0002015818,0.0000623443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003470598,0.0002031204,0.001679965,0.0001935917,0.0002191178,0.0002564568,0.000110479,0.7306001,0.005887487,0.009139087,0.01008845,0.2412751],"study_design_scores_gemma":[0.0000179242,0.00004895067,0.0003345546,0.00000466042,0.00001610209,0.00002912888,0.0000190323,0.9927504,0.00113263,0.004302753,0.001336686,0.00000713229],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0121395,0.0001992823,0.9850037,0.0001044008,0.00005949371,0.00006972555,0.000185408,0.000952105,0.001286325],"genre_scores_gemma":[0.2708139,0.000256491,0.7195288,0.0001946722,0.0002251773,0.0005828546,0.00208379,0.0007821184,0.005532215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007584868,"threshold_uncertainty_score":0.02537394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635061599885774,"score_gpt":0.239574373959165,"score_spread":0.2232237579603072,"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."}}