{"id":"W143286093","doi":"10.5006/c2009-09097","title":"The Introduction of KIAPPLIED to TM0177 Method D (DCB) and Use of “Offspec” Results","year":2009,"lang":"en","type":"article","venue":"","topic":"Engineering and Material Science Research","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shell (Canada)","funders":"","keywords":"Computer science; Materials science","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":[0.001387285,0.00005120727,0.0001063481,0.00004344906,0.00005799158,0.00005984972,0.0001435747,0.00002319533,0.00002572981],"category_scores_gemma":[0.0003991196,0.00003044758,0.00001231591,0.0001775909,0.0000613719,0.00009741721,0.0000481178,0.0000282464,0.00000710808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001066604,"about_ca_system_score_gemma":0.00001474672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001582581,"about_ca_topic_score_gemma":0.0000107256,"domain_scores_codex":[0.9992045,0.00004442427,0.0001981624,0.0001665419,0.0002138234,0.000172547],"domain_scores_gemma":[0.9994687,0.0001226494,0.00004052819,0.0002329517,0.00007103296,0.00006410002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008698623,0.000009743893,0.000001549718,0.000005119593,7.708417e-7,1.133916e-7,0.0001004883,0.0006655013,0.9813107,0.008524633,0.001488417,0.007805948],"study_design_scores_gemma":[0.0000977269,0.000142133,0.001726442,0.000004654206,0.00000185071,0.000001801399,0.00004588958,0.0003111825,0.9867983,0.000441609,0.01038545,0.00004296687],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982032,0.0000162323,0.01241186,0.004134091,0.0002200222,0.0001991245,0.00001043223,0.00003767336,0.0009385709],"genre_scores_gemma":[0.9504103,0.00003356364,0.04860193,0.00002149178,0.0001047621,0.00000298323,7.563406e-7,0.000002895489,0.0008213277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03619008,"threshold_uncertainty_score":0.1241616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620924803953621,"score_gpt":0.3202385621337772,"score_spread":0.294029314094241,"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."}}