{"id":"W2811084878","doi":"10.2514/6.2018-3520","title":"F-35 Information Fusion","year":2018,"lang":"en","type":"article","venue":"2018 Aviation Technology, Integration, and Operations Conference","topic":"Engineering and Test Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Fusion; Computer science; Information fusion; 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":[0.001524119,0.001381002,0.0009936085,0.002472126,0.001687551,0.003538877,0.001137654,0.002154724,0.05254867],"category_scores_gemma":[0.003276755,0.0004169565,0.001267988,0.002036655,0.0008479337,0.002757406,0.002809794,0.00120575,0.02182274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163005,"about_ca_system_score_gemma":0.002224189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006023062,"about_ca_topic_score_gemma":0.003531108,"domain_scores_codex":[0.9986443,0.0001899056,0.00006367947,0.0003183135,0.0005848494,0.000198936],"domain_scores_gemma":[0.9988587,0.0001402897,0.00003793995,0.0004087285,0.0004852092,0.00006914406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001290386,0.0001309721,0.001514281,0.0003311207,0.000254639,0.0004598287,0.0001949944,0.01861423,0.03332125,0.1367156,0.1663037,0.640869],"study_design_scores_gemma":[0.000138552,0.0004303158,0.002921168,0.0002092768,0.0002296296,0.0008781252,0.0002205809,0.2029791,0.102576,0.168852,0.5203281,0.0002371994],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01598997,0.003380403,0.6551538,0.002628534,0.003158917,0.0004327269,0.007984534,0.01402856,0.2972426],"genre_scores_gemma":[0.4851178,0.002438809,0.32616,0.001840012,0.001186177,0.0003637337,0.02258075,0.001910083,0.1584027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05254867,"threshold_uncertainty_score":0.1757928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007322458183724591,"score_gpt":0.2034056589659845,"score_spread":0.1960832007822599,"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."}}