{"id":"W4317000346","doi":"10.1145/3573074.3573078","title":"On COVID-19 Pandemic-Induced Attitudinal Changes in Software Engineering Teaching and Learning","year":2023,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Persona Design and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Ephemeral key; Perspective (graphical); Software; Transformation (genetics); Computer science; Mathematics education; Software engineering; Knowledge management; Engineering ethics; Engineering; Psychology; Medicine; Chemistry; Artificial intelligence; Computer security","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008493187,0.000320917,0.0002840973,0.0005545381,0.0003113171,0.0001548521,0.0007664068,0.0001477767,0.000004819196],"category_scores_gemma":[0.1251679,0.0003503728,0.00005310701,0.0007929991,0.00001604807,0.0002622134,0.0004399445,0.0009793594,0.00004233129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001714985,"about_ca_system_score_gemma":0.00006050487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000856074,"about_ca_topic_score_gemma":0.00001723417,"domain_scores_codex":[0.998211,0.00006184958,0.0002230844,0.0006375355,0.0002817832,0.0005847636],"domain_scores_gemma":[0.9628509,0.03625055,0.00006019679,0.0005416764,0.00002377624,0.0002728432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001740916,0.0001072667,0.7500265,0.0006508831,0.00008295944,0.0002353075,0.008653169,0.1136828,0.04125801,0.008470461,0.0005480744,0.07626712],"study_design_scores_gemma":[0.002813626,0.0006290678,0.8050902,0.00111602,0.00004890997,0.0002989685,0.0002186904,0.1651033,0.002610379,0.0005483505,0.01795202,0.003570506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7461851,0.0001581676,0.2488151,0.0008097257,0.0001751782,0.0002229663,0.000006743606,0.003625832,0.000001188927],"genre_scores_gemma":[0.9364523,0.00003356069,0.06287578,0.0002966586,0.00009572167,0.0001369209,0.00001811001,0.00004761609,0.00004332271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1902672,"threshold_uncertainty_score":0.9998948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05275108883853901,"score_gpt":0.2909140502523543,"score_spread":0.2381629614138153,"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."}}