{"id":"W2739443880","doi":"10.1079/tourism.2022.0026","title":"Robotics Programming Kids for Leisure","year":2022,"lang":"en","type":"article","venue":"Tourism Cases","topic":"Child Welfare and Adoption","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Excellence; Government (linguistics); Logo (programming language); Sociology; Political science; Pedagogy; Social science; Law; Computer science","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":[0.0005113803,0.0003617388,0.0001781906,0.0005812573,0.002793881,0.001335404,0.0007951056,0.0005637414,0.1127537],"category_scores_gemma":[0.001230563,0.0002151922,0.000495267,0.0002994341,0.001149816,0.001390541,0.003337177,0.001716931,0.02515432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068588,"about_ca_system_score_gemma":0.002093242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008279875,"about_ca_topic_score_gemma":0.02939594,"domain_scores_codex":[0.999463,0.0001148019,0.00002031148,0.00007400283,0.0001116483,0.0002163052],"domain_scores_gemma":[0.9988924,0.00006087058,0.00007640475,0.00007122813,0.0001158963,0.0007832372],"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":[0.0001038152,0.002001728,0.05336281,0.0005096734,0.00001917698,0.005498565,0.04068353,0.000342755,0.002129793,0.02746765,0.5048257,0.3630549],"study_design_scores_gemma":[0.00002692594,0.0003087753,0.02653317,0.0003857071,0.00001195563,0.005007776,0.03217179,0.0003576463,0.0007654012,0.003645344,0.9307457,0.00003975094],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1849002,0.0006602528,0.005770674,0.01465463,0.0007518554,0.0003912844,0.0007718013,0.001077235,0.7910222],"genre_scores_gemma":[0.3858619,0.001476676,0.01291747,0.004068201,0.00009554973,0.0005282041,0.0007351552,0.0002627033,0.5940542],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1127537,"threshold_uncertainty_score":0.3771986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614027422956294,"score_gpt":0.3159279684147864,"score_spread":0.2797876941852235,"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."}}