{"id":"W4220799416","doi":"10.1029/2021jb022825","title":"Pair Selection Optimization for InSAR Time Series Processing","year":2022,"lang":"en","type":"article","venue":"Journal of Geophysical Research Solid Earth","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Belgian Federal Science Policy Office","keywords":"Interferometric synthetic aperture radar; Synthetic aperture radar; Computer science; Interferometry; Remote sensing; Algorithm; Time series; Artificial intelligence; Geology; Data mining; Machine learning","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":[0.001317582,0.001727111,0.001212911,0.001319569,0.0005353359,0.001004177,0.001125914,0.000947253,0.006247091],"category_scores_gemma":[0.003532944,0.000549397,0.001062147,0.001587256,0.0005460649,0.000836015,0.001033673,0.001058526,0.001454918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005618637,"about_ca_system_score_gemma":0.0008348111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002925084,"about_ca_topic_score_gemma":0.002524305,"domain_scores_codex":[0.9988335,0.0005528861,0.00004506476,0.0002242399,0.0002395096,0.0001049156],"domain_scores_gemma":[0.9982627,0.001205052,0.0001005546,0.0001164259,0.0002494534,0.00006586004],"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":[0.0003157126,0.0001891332,0.001527935,0.0001455736,0.0001660375,0.0002032335,0.00007071826,0.8071931,0.004963567,0.005953511,0.006266421,0.1730051],"study_design_scores_gemma":[0.00001052909,0.00002937901,0.0002498073,0.000002986944,0.00001051353,0.00001355511,0.00001205525,0.9963953,0.0007300558,0.001996776,0.0005449799,0.000004165062],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02535271,0.0002494722,0.9714494,0.0001481676,0.00006673846,0.00006994977,0.0002108997,0.0009557144,0.001497025],"genre_scores_gemma":[0.4271792,0.0002120174,0.5647863,0.0001853149,0.0001808097,0.000415948,0.001876994,0.0005462239,0.004617288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006247091,"threshold_uncertainty_score":0.02089864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180282708526234,"score_gpt":0.3019405308162033,"score_spread":0.2839122599635798,"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."}}