{"id":"W2216176025","doi":"10.1145/2807565.2807716","title":"Girls Learning Computer Science Principles with After School Games","year":2015,"lang":"en","type":"article","venue":"","topic":"Educational Games and Gamification","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"National Science Foundation","keywords":"Computer science; Mathematics education; Multimedia; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001287895,0.0008115027,0.0005625815,0.0004720757,0.000970551,0.001963419,0.0008813093,0.0008912804,0.01296547],"category_scores_gemma":[0.002920506,0.0002750918,0.0008022797,0.0002912231,0.0007214339,0.001162573,0.001808897,0.002044282,0.002465031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004258385,"about_ca_system_score_gemma":0.0004928243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0010989,"about_ca_topic_score_gemma":0.002092264,"domain_scores_codex":[0.9992598,0.0002099465,0.00004337194,0.0001790519,0.0001257381,0.0001820357],"domain_scores_gemma":[0.9978355,0.0006946254,0.0001868119,0.0002335411,0.0001329733,0.0009166725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007510272,0.110989,0.1365571,0.00183019,0.0006382118,0.002802965,0.03980612,0.005354614,0.07610621,0.05208293,0.03570634,0.5306159],"study_design_scores_gemma":[0.004786359,0.07492553,0.2754577,0.001139975,0.0007999227,0.00348617,0.03631866,0.01361651,0.1384885,0.06812018,0.3825098,0.0003507744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672295,0.0001135411,0.006150547,0.0009952087,0.0001273446,0.0004113374,0.0002299244,0.0002168021,0.02452565],"genre_scores_gemma":[0.9447207,0.0003162256,0.0227004,0.0006919783,0.00004153024,0.0005626827,0.0003006126,0.0001242705,0.03054146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01296547,"threshold_uncertainty_score":0.04337382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441336627594008,"score_gpt":0.3273464102889833,"score_spread":0.2832127475295825,"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."}}