{"id":"W4210588147","doi":"10.1145/3511322.3511327","title":"AI education matters","year":2021,"lang":"en","type":"article","venue":"AI Matters","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact; University of Toronto","funders":"","keywords":"Autoencoder; Artificial intelligence; Computer science; Sentence; Sequence (biology); Deep learning; Ideal (ethics); Word (group theory); Artificial neural network; Noise reduction; Natural language processing; Linguistics","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":[0.00006569879,0.00007352434,0.00007325728,0.00004774295,0.00004919,0.000170321,0.0003536529,0.0000256214,0.00008988516],"category_scores_gemma":[0.000003368842,0.00007926139,0.00003747041,0.000153381,0.00001175668,0.0003750945,0.0001365758,0.00008917809,0.0003349317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004139873,"about_ca_system_score_gemma":0.0001527971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004480427,"about_ca_topic_score_gemma":0.000004910063,"domain_scores_codex":[0.9992527,0.00003268617,0.0001239577,0.0002788524,0.0001425422,0.0001692327],"domain_scores_gemma":[0.9993173,0.0000177914,0.00002856277,0.0005242942,0.00005409536,0.00005793628],"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":[4.279e-7,0.00003507541,0.0001375925,0.00002072682,0.000008517524,0.00001333907,0.0004836368,0.000195648,0.002084075,0.01858216,0.9443412,0.03409763],"study_design_scores_gemma":[0.0001890451,0.000009552795,0.0008045987,0.00006158261,0.000007799654,0.00009076785,0.0001252533,0.02142855,0.005303068,0.01102093,0.9606643,0.0002945873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0008050468,0.00003450673,0.4216526,0.5764936,0.0007905495,0.00002873135,2.560035e-7,0.00006522056,0.000129451],"genre_scores_gemma":[0.03035907,0.000002941857,0.03091584,0.9371825,0.00008692868,0.00001007264,0.000003482535,0.000007782078,0.00143137],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3907368,"threshold_uncertainty_score":0.4304981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100292593406565,"score_gpt":0.2575460242079157,"score_spread":0.24654309827385,"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."}}