{"id":"W3118430865","doi":"10.2514/6.2021-0916","title":"5<sup>th</sup>Generation Fusion Test Framework","year":2021,"lang":"en","type":"article","venue":"AIAA Scitech 2021 Forum","topic":"Engineering and Test Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Integration testing; Computer science; Consistency (knowledge bases); Taxonomy (biology); Sensor fusion; Implementation; Software engineering; Fusion; Systems engineering; Data integration; System integration; Strengths and weaknesses; System testing; Data mining; Database; Operating system; Engineering; Software; Artificial intelligence","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":[0.003244423,0.0008578402,0.0004927043,0.0016519,0.001056466,0.003678614,0.002668615,0.001932784,0.1272878],"category_scores_gemma":[0.004426589,0.0004607706,0.000903622,0.0006763177,0.001253962,0.002641145,0.002448777,0.001784768,0.04622926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001981887,"about_ca_system_score_gemma":0.001914961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008728539,"about_ca_topic_score_gemma":0.00741468,"domain_scores_codex":[0.9985611,0.0003421881,0.00008102386,0.0001575669,0.0006700375,0.0001880637],"domain_scores_gemma":[0.9981078,0.0004395843,0.00007235885,0.0004599623,0.0007398488,0.0001804967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005529817,0.000253057,0.002750142,0.0004683015,0.00005009922,0.001089499,0.0006449022,0.02943961,0.01753544,0.1999606,0.3266201,0.4206352],"study_design_scores_gemma":[0.0000861948,0.000248199,0.001639694,0.0003709815,0.00003101238,0.0008820932,0.000354437,0.105524,0.02837234,0.06157199,0.8008308,0.00008815029],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003359894,0.0003487755,0.7316368,0.00169492,0.0006504367,0.0009676296,0.00410321,0.03892475,0.2183136],"genre_scores_gemma":[0.163364,0.0007052731,0.6507963,0.001919495,0.000380695,0.001373634,0.01958442,0.01331703,0.1485592],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1272878,"threshold_uncertainty_score":0.4258202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008015923867464678,"score_gpt":0.2022033391061672,"score_spread":0.1941874152387025,"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."}}