{"id":"W2332713829","doi":"10.1117/12.786795","title":"Front Matter: Volume 6800","year":2007,"lang":"en","type":"paratext","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Near-Field Optical Microscopy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Università degli Studi di Salerno; North Carolina State University; University of South Australia; Uppsala Universitet; Centre National de la Recherche Scientifique; University of Toronto; University of New South Wales; Rijksuniversiteit Groningen; Imperial College London; Australian National University; Commonwealth Scientific and Industrial Research Organisation; University of Canterbury","keywords":"Volume (thermodynamics); Front (military); Computer science; Environmental science; Physics; Meteorology; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006549451,0.000953789,0.001186765,0.0002673635,0.00009920562,0.0002717631,0.002105183,0.001053642,0.001364089],"category_scores_gemma":[0.000251221,0.000883047,0.001431076,0.0003775036,0.0003706866,0.000529607,0.0003368391,0.001422697,0.0007816009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005251627,"about_ca_system_score_gemma":0.00005741301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001824715,"about_ca_topic_score_gemma":2.616876e-7,"domain_scores_codex":[0.9955925,1.364019e-8,0.001507439,0.0007378868,0.001106943,0.001055177],"domain_scores_gemma":[0.9972395,0.0001981761,0.0004597846,0.0001620873,0.001633984,0.0003064245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009762149,0.0001263281,0.00009493194,0.003270472,0.001340128,3.849062e-7,0.0001722608,0.0007874304,0.3118238,0.02801959,0.6539508,0.0003163423],"study_design_scores_gemma":[0.002274357,0.0006064477,0.0004514057,0.002551123,0.0008208821,0.00006671218,0.0008701912,0.04184062,0.3054601,0.0006649978,0.6416504,0.002742734],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8656796,0.001131414,0.0002405946,0.0009994473,0.002819638,0.001091546,0.0003676989,0.000245085,0.1274249],"genre_scores_gemma":[0.07649485,0.004859653,0.7198694,0.001840184,0.01411735,0.001755382,0.000536284,0.002651846,0.1778751],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7891848,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008348893494482978,"score_gpt":0.2292127846279857,"score_spread":0.2208638911335027,"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."}}