{"id":"W4399663116","doi":"10.1117/12.3019692","title":"METIS high-contrast imaging: from final design to manufacturing and testing","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Semiconductor Detectors and Materials","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Metis; Contrast (vision); Computer science; Artificial intelligence; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000598113,0.0001335427,0.0001333692,0.00005867844,0.00002889486,0.0001465611,0.00005329431,0.00002394628,0.0001905771],"category_scores_gemma":[0.00001975239,0.00011733,0.00001297559,0.0000476063,0.000008606105,0.0001604936,0.00002923683,0.00006384687,0.00004363448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003075356,"about_ca_system_score_gemma":0.000004663244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001234982,"about_ca_topic_score_gemma":0.000004936982,"domain_scores_codex":[0.9994267,0.000008333806,0.0001288947,0.0001925015,0.00005407363,0.0001895463],"domain_scores_gemma":[0.9996473,0.0001728169,0.000005297117,0.00008880531,0.00000676672,0.00007902233],"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":[0.000002455443,9.149186e-7,0.00001391968,0.00002225061,0.00001542211,0.0000275523,0.00006785386,0.002345613,0.942001,0.00002651383,0.0004890586,0.05498743],"study_design_scores_gemma":[0.0000826103,0.00001119136,0.0006955952,0.00006666459,0.00001471083,0.00001096653,0.00001991706,0.008507093,0.9873034,0.001686941,0.001418181,0.0001827812],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.770668,0.000619992,0.2270376,0.00002046177,0.0006228032,0.00010853,0.00002064154,0.0006846857,0.0002172843],"genre_scores_gemma":[0.9302174,0.00001149454,0.06942546,0.00003952563,0.0001783223,0.00001295413,0.000002404111,0.00003642736,0.00007601325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1595494,"threshold_uncertainty_score":0.4784577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807897037910874,"score_gpt":0.2258814433144375,"score_spread":0.1978024729353287,"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."}}