{"id":"W2346423261","doi":"10.1117/12.2213454","title":"Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Digital Holography and Microscopy","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Digital holographic microscopy; Phase imaging; Microscopy; Holography; Modality (human–computer interaction); Computer science; Phase (matter); Digital holography; Biological system; Materials science; Optics; Artificial intelligence; Physics; Biology","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":[0.0009834615,0.0005176481,0.0004341901,0.001512731,0.0001494915,0.0008737015,0.0006462344,0.00057384,0.001843635],"category_scores_gemma":[0.0008435935,0.0002941377,0.0002580869,0.0009584133,0.00091714,0.001256731,0.0008129369,0.0006074561,0.0005347252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003959294,"about_ca_system_score_gemma":0.0005455953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000253007,"about_ca_topic_score_gemma":0.0003236105,"domain_scores_codex":[0.9996197,0.00006406174,0.00001903195,0.00007746149,0.0001989973,0.00002068616],"domain_scores_gemma":[0.9995437,0.0001780632,0.00007469732,0.00009082011,0.00008314633,0.00002952549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001731182,0.00006182175,0.001289049,0.0008682631,0.00004488317,0.0001292249,0.0001036845,0.001690621,0.784019,0.02003443,0.003404327,0.1881817],"study_design_scores_gemma":[0.0001123469,0.0004623619,0.005367158,0.0001433672,0.0001263922,0.002974557,0.000123429,0.04735573,0.831014,0.01623285,0.0959714,0.0001165102],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04334509,0.02760406,0.9136617,0.001652025,0.0005822396,0.0001960877,0.001215968,0.001867443,0.00987533],"genre_scores_gemma":[0.3034212,0.01914249,0.6666706,0.001298578,0.0008001255,0.0002262905,0.0006751266,0.0002234116,0.007542154],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001843635,"threshold_uncertainty_score":0.006167591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097407193175932,"score_gpt":0.2796784462968649,"score_spread":0.2687043743651056,"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."}}