{"id":"W4243496875","doi":"10.1117/3.853623.ch88","title":"MTF Measurement Techniques: Noiselike Targets","year":2010,"lang":"en","type":"book-chapter","venue":"SPIE eBooks","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001043861,0.0006293891,0.0005913311,0.0004288164,0.0002405225,0.00009944086,0.002037989,0.001404569,0.00008793972],"category_scores_gemma":[0.00004536251,0.0005980689,0.0002854831,0.00002480718,0.0002183819,0.00008416785,0.000171392,0.001424815,0.0005142408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002069828,"about_ca_system_score_gemma":0.0002077203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001773848,"about_ca_topic_score_gemma":0.0001016001,"domain_scores_codex":[0.996578,0.0000151139,0.0006045685,0.0009983446,0.001267592,0.0005363303],"domain_scores_gemma":[0.9967709,0.00001995519,0.0004316785,0.00220318,0.0004025006,0.000171821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009698681,0.00003179567,0.00000863046,0.00009086924,0.0002075988,0.0001572715,0.0001618524,6.339694e-8,0.1509092,0.7419055,0.01047701,0.09604055],"study_design_scores_gemma":[0.0001707317,0.0001073388,0.000004692817,0.0002764837,0.00003693336,0.00004974856,0.000001755276,0.000003870587,0.1535944,0.04625211,0.7988954,0.0006065064],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001172167,0.0006272814,0.02433323,0.0003341305,0.002404922,0.001052803,0.000005964266,0.002083365,0.9691466],"genre_scores_gemma":[0.01504399,0.00004514543,0.04397941,0.001371976,0.001218322,0.000254483,0.000008405429,0.000208387,0.9378699],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7884184,"threshold_uncertainty_score":0.9998918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03649438556162011,"score_gpt":0.2245845761917287,"score_spread":0.1880901906301086,"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."}}