{"id":"W7053562160","doi":"","title":"Young people not in education, employment or training (NEET), UK, Aug 2016","year":2016,"lang":"en","type":"other","venue":"Digital Education Resource Archive (University College London)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Table (database); Statistical analysis; Young adult; Training (meteorology); Quarter (Canadian coin); Percentage point","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":[0.001102793,0.0008846603,0.0005101023,0.00339026,0.0004285952,0.001437053,0.0006794611,0.0004707142,0.03396221],"category_scores_gemma":[0.00895231,0.0006006108,0.0007074023,0.005031683,0.0002524203,0.00145668,0.00180378,0.0008097251,0.01923597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002551923,"about_ca_system_score_gemma":0.00300815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2007978,"about_ca_topic_score_gemma":0.2293544,"domain_scores_codex":[0.9982498,0.0001282524,0.0004794478,0.00018201,0.0007413817,0.0002190691],"domain_scores_gemma":[0.9960451,0.0003725467,0.0008731135,0.0001387656,0.002160245,0.0004102739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002048583,0.00001542869,0.02061749,0.001459675,0.00003240964,0.00005667374,0.0003110233,0.0001377573,0.00007598684,0.000522188,0.9450641,0.03150229],"study_design_scores_gemma":[0.0001038141,0.00007973077,0.3532996,0.001902274,0.00004550111,0.0001439004,0.001135525,0.0001295678,0.0002073509,0.0002377039,0.6426792,0.000035891],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01455345,0.006080968,0.0003561456,0.001827053,0.001383926,0.0001893509,0.9482442,0.0002524913,0.02711239],"genre_scores_gemma":[0.05263012,0.01666589,0.001388916,0.001496599,0.0008451749,0.001429737,0.7803669,0.0003443359,0.1448324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2007978,"threshold_uncertainty_score":0.399258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008340124896282223,"score_gpt":0.2044053368535109,"score_spread":0.1960652119572286,"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."}}