{"id":"W4402474466","doi":"10.1109/ccece59415.2024.10667239","title":"Oral Interviews to Preserve the History of Engineering Accomplishments in Canada","year":2024,"lang":"en","type":"article","venue":"","topic":"Research, Science, and Academia","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Council of Professional Engineers","funders":"Western University","keywords":"Oral history; Computer science; Engineering ethics; Engineering; History; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003025139,0.0000645062,0.0001416363,0.0002287875,0.00001478777,0.00008364723,0.001608939,0.00001574783,0.0008615532],"category_scores_gemma":[0.001058069,0.0000325685,0.00004148385,0.0008974248,0.00003598273,0.000291642,0.0003448375,0.0001967503,0.00007069485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007135084,"about_ca_system_score_gemma":0.001105433,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6507232,"about_ca_topic_score_gemma":0.7812818,"domain_scores_codex":[0.9977393,0.00007619752,0.0004020234,0.0002649059,0.001282462,0.0002350932],"domain_scores_gemma":[0.9988095,0.0006742445,0.00002381863,0.0003315404,0.00005684675,0.0001040327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004725096,0.000006651719,0.007977172,0.00001463655,0.000004808386,0.00001442889,0.001721574,0.002054366,0.001055456,0.001073797,0.9306184,0.05545396],"study_design_scores_gemma":[0.00004261292,0.00001332073,0.03117567,0.00004929102,7.827136e-7,0.000001273631,0.0008832308,0.04888837,0.0003329716,0.0006306246,0.9179099,0.00007199235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327859,0.003212275,0.00150524,0.008191135,0.004279939,0.0005018157,0.00001244812,0.0000296525,0.04948166],"genre_scores_gemma":[0.9783926,0.000008440796,0.0001639638,0.0003319511,0.00002243036,0.00001123963,1.635796e-7,0.000003440035,0.02106579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1305585,"threshold_uncertainty_score":0.9433403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2078572206696181,"score_gpt":0.403704617404905,"score_spread":0.1958473967352869,"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."}}