{"id":"W4399666198","doi":"10.1117/12.3020823","title":"Large Bondspot RTV Adhesion for NFIRAOS OAPs","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ABB (Canada); National Research Council Canada","funders":"","keywords":"Adhesion; Computer science; Materials science; Composite material","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":[0.0001944132,0.0001123461,0.00009365974,0.0001250898,0.00002992944,0.00006440384,0.0001116899,0.00007775516,0.00026036],"category_scores_gemma":[0.00001595709,0.00009963675,0.00006133894,0.0001907695,0.000006150698,0.00006193865,0.00002678536,0.0001791999,0.0005357445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005621101,"about_ca_system_score_gemma":0.00001140109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001619422,"about_ca_topic_score_gemma":0.000003163214,"domain_scores_codex":[0.9992337,0.000002554258,0.000110867,0.0001541315,0.000137015,0.0003617493],"domain_scores_gemma":[0.9996334,0.0001067585,0.000001682384,0.000168046,0.00001428159,0.00007580985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001775401,0.00005268807,0.00002990501,0.003879481,0.0002056202,0.00005967089,0.0006124342,0.0448989,0.2754012,0.1638187,0.4794488,0.03157488],"study_design_scores_gemma":[0.0001586556,0.00002237074,0.00003456917,0.0000432414,0.000006260967,0.000003471907,0.00003758967,0.5361334,0.05000441,0.0004304526,0.4129651,0.0001604658],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08353174,0.005544413,0.7666566,0.0005811054,0.00241649,0.001350128,0.0001042229,0.01071682,0.1290984],"genre_scores_gemma":[0.9902507,0.00005727627,0.003755895,0.00001711837,0.0002310934,0.0001425528,0.00001759997,0.00008835919,0.005439383],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.906719,"threshold_uncertainty_score":0.6886091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260413802963584,"score_gpt":0.2644531620427736,"score_spread":0.2518490240131378,"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."}}