{"id":"W3185652110","doi":"10.1017/pds.2021.60","title":"CARDINAL WTRL: TECHNOLOGY MATURITY, SCHEDULE SLIPPAGE AND TREND FORECASTING.","year":2021,"lang":"en","type":"article","venue":"Proceedings of the Design Society","topic":"Technology Assessment and Management","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Maturity (psychological); Schedule; Computer science; Process (computing); Operations research; Industrial engineering; Process management; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001883858,0.0001284172,0.000175904,0.00004096415,0.00009653488,0.0000295438,0.0002297509,0.0001788784,0.000006823658],"category_scores_gemma":[0.00002699157,0.0001089834,0.0001009651,0.0004228848,0.0001382414,0.0001036509,0.0002914468,0.0002525224,6.916718e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003645976,"about_ca_system_score_gemma":0.000009077753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.413872e-7,"about_ca_topic_score_gemma":4.876757e-7,"domain_scores_codex":[0.9993578,0.000002357037,0.000139038,0.000171317,0.0001151426,0.0002143925],"domain_scores_gemma":[0.9997534,0.00001717862,0.00005030174,0.0001002845,0.00005787658,0.00002095375],"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":[0.00002143466,0.0001860586,0.03624597,0.002048641,0.001515502,0.000009787181,0.002427578,0.0003562206,0.6917949,0.09771169,0.1385385,0.02914364],"study_design_scores_gemma":[0.001376311,0.00009087662,0.004246975,0.0002628963,0.000378194,0.0001595161,0.006393836,0.04065483,0.8949732,0.03758916,0.01320148,0.0006727879],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981393,0.002073742,0.005466592,0.002241291,0.000311123,0.0003680026,0.000006752324,0.0009180151,0.007221517],"genre_scores_gemma":[0.9524847,0.0001971233,0.04700073,0.00002738862,0.00002706941,0.00002892077,6.439335e-7,0.00002061752,0.0002128361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2031782,"threshold_uncertainty_score":0.4444215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01640650805161066,"score_gpt":0.2010762470587755,"score_spread":0.1846697390071649,"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."}}