{"id":"W2099025359","doi":"10.1109/isot.2010.5687314","title":"Dynamic phase measurement by clustering method","year":2010,"lang":"en","type":"article","venue":"","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Cluster analysis; Phase retrieval; Speckle noise; Speckle pattern; Shearography; Phase (matter); Robustness (evolution); Metrology; Phase noise; Holography; Interferometry; Artificial intelligence; Computer vision; Fourier transform; Algorithm; Optics; Mathematics; Physics","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":[0.0005743519,0.0009509547,0.0008937203,0.002392597,0.0007599168,0.001062605,0.001483466,0.001020787,0.003417885],"category_scores_gemma":[0.001671438,0.0004939074,0.0007710059,0.002640649,0.0006892213,0.001911751,0.0012497,0.0009676024,0.002149279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008773471,"about_ca_system_score_gemma":0.0007946661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001846724,"about_ca_topic_score_gemma":0.001383065,"domain_scores_codex":[0.9985036,0.0001807784,0.00006761072,0.0004674398,0.0006775223,0.000103118],"domain_scores_gemma":[0.9991152,0.0001376357,0.00008232812,0.0001765304,0.000457274,0.00003113795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001740948,0.00008088135,0.0008950995,0.0003443355,0.0001030436,0.00009538217,0.0002755146,0.07434896,0.1324744,0.034038,0.005388957,0.7517814],"study_design_scores_gemma":[0.00004534559,0.0001132872,0.001234731,0.00003346318,0.00006621048,0.0003692903,0.0001035805,0.8625821,0.09996992,0.0173671,0.0179802,0.0001347775],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003725444,0.000132176,0.9938632,0.00004547026,0.00004314121,0.00003877012,0.0000389538,0.0005452884,0.001567538],"genre_scores_gemma":[0.1099903,0.000429503,0.8840193,0.00008165764,0.00007723327,0.0001579106,0.0002946519,0.0002839272,0.004665625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003417885,"threshold_uncertainty_score":0.01143396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03994460045719863,"score_gpt":0.3399363754641455,"score_spread":0.2999917750069468,"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."}}