{"id":"W2604575007","doi":"10.1145/3017680.3022434","title":"What We Say vs. What They Do","year":2017,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outreach; Mainstream; Variety (cybernetics); Diversification (marketing strategy); Computer science; Coding (social sciences); Public relations; World Wide Web; Sociology; Social science; Political science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01882709,0.000502556,0.0007215553,0.00199888,0.004781744,0.01498256,0.001396593,0.003432501,0.01501655],"category_scores_gemma":[0.06767099,0.0003723754,0.0005920242,0.001932188,0.01877993,0.02443663,0.004460113,0.00822476,0.005801374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003516887,"about_ca_system_score_gemma":0.006770386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004475213,"about_ca_topic_score_gemma":0.00425471,"domain_scores_codex":[0.9765975,0.01329726,0.001217377,0.002042434,0.004957766,0.001887723],"domain_scores_gemma":[0.9531872,0.02632955,0.004418909,0.002911943,0.007754066,0.005398326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001662541,0.0001467563,0.01483799,0.002278879,0.0002156747,0.0007401832,0.2061751,0.0001916285,0.0008709482,0.4184681,0.1732912,0.1826172],"study_design_scores_gemma":[0.00003344725,0.00007179494,0.003446111,0.003001844,0.00009748452,0.0006692595,0.1532913,0.0001967066,0.0006834085,0.2282558,0.6101695,0.00008332323],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03687045,0.0266747,0.02343248,0.6140819,0.02499833,0.0002012406,0.0007967244,0.0002456041,0.2726986],"genre_scores_gemma":[0.6832364,0.03270907,0.01630796,0.2059276,0.01067428,0.0005894312,0.0006458053,0.0007936476,0.04911589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01882709,"threshold_uncertainty_score":0.09956837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02721729491054234,"score_gpt":0.2914630055201056,"score_spread":0.2642457106095633,"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."}}