{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007199473,0.0006187459,0.0002672165,0.0003573215,0.0005446069,0.0007745643,0.001002615,0.0005749755,0.005483091],"category_scores_gemma":[0.002048315,0.0004362583,0.0003513922,0.0001960312,0.0002839746,0.0007507524,0.0005604973,0.0006184089,0.001087883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006397235,"about_ca_system_score_gemma":0.000557796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008974454,"about_ca_topic_score_gemma":0.002543681,"domain_scores_codex":[0.9991592,0.00005918004,0.000039926,0.00009123825,0.0005430772,0.0001074374],"domain_scores_gemma":[0.9990669,0.0001724399,0.0001961285,0.0001385668,0.0003592922,0.00006670984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001963246,0.0001775396,0.004302799,0.0007227632,0.00004966832,0.0008323913,0.0007777791,0.02568992,0.8489445,0.006702548,0.006046384,0.1055572],"study_design_scores_gemma":[0.00009535551,0.005035167,0.0175657,0.0002259961,0.0001266963,0.001657375,0.0008469548,0.09156255,0.7805101,0.001844065,0.1003563,0.0001736809],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8245596,0.0008402056,0.1419713,0.0003971493,0.0009145639,0.0005063579,0.0004234848,0.001528147,0.02885916],"genre_scores_gemma":[0.9070792,0.0004143983,0.07697487,0.00004567391,0.0000308358,0.0002109867,0.0002400847,0.000310555,0.01469345],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005483091,"threshold_uncertainty_score":0.01834279,"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."}}