{"id":"W3211012387","doi":"10.3390/app112110041","title":"A Contrast Calibration Protocol for X-ray Speckle Visibility Spectroscopy","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"U.S. Department of Energy","keywords":"Visibility; Optics; Detector; Speckle pattern; Calibration; Pixel; Physics; Photon; Contrast (vision); Computer science; Noise (video); Photon counting; Artificial intelligence; Image (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000275907,0.0001142001,0.0001426743,0.00002512168,0.0002661342,0.0001431606,0.0001963234,0.00001746978,0.0002282474],"category_scores_gemma":[0.00001184408,0.00009892909,0.00004927547,0.0002449133,0.0002167337,0.0002093576,0.0000475727,0.00007119525,0.00000647385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000204509,"about_ca_system_score_gemma":0.0001708486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009809508,"about_ca_topic_score_gemma":0.000003764672,"domain_scores_codex":[0.9989483,0.00001678327,0.000185255,0.0004202393,0.0001685135,0.0002608939],"domain_scores_gemma":[0.9995148,0.00008199638,0.00008984135,0.0002118615,0.00005418757,0.00004726678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004632842,0.0002968189,0.009246802,0.00003069544,0.00001552322,7.566782e-7,0.0001890822,0.0001974978,0.4681886,0.5129687,0.002775357,0.00604385],"study_design_scores_gemma":[0.0004695598,0.00005033223,0.000298868,0.00001075333,0.000004519495,2.568901e-7,0.0002489139,0.001821225,0.7574775,0.2320963,0.007362342,0.0001594747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004830628,0.000001449466,0.9194896,0.0003724552,0.00004219197,0.04732243,0.00002204528,0.0001490846,0.02777016],"genre_scores_gemma":[0.6105546,3.65043e-8,0.2584865,0.000120842,0.0002322355,0.1304622,0.00001139167,0.00001055731,0.0001216194],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6610031,"threshold_uncertainty_score":0.4034211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02552185362876545,"score_gpt":0.3527420045007315,"score_spread":0.327220150871966,"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."}}