{"id":"W2279102082","doi":"","title":"The Electro-Motive Lockout and Non-Occupation: What Did We Lose? What Can We Learn?","year":2013,"lang":"en","type":"article","venue":"Alternate routes","topic":"Disability Education and Employment","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Psychology; Social psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.00527128,0.0004664437,0.0009795116,0.0009796199,0.002951798,0.007850053,0.002344236,0.004365059,0.02273675],"category_scores_gemma":[0.01746153,0.0003175839,0.0009004956,0.001027733,0.009284631,0.01377081,0.004868468,0.00664634,0.001737049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002704265,"about_ca_system_score_gemma":0.009172101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02149669,"about_ca_topic_score_gemma":0.03806214,"domain_scores_codex":[0.9977618,0.0009412692,0.00008969485,0.0001879032,0.000405276,0.0006139921],"domain_scores_gemma":[0.9899746,0.004616002,0.0009148687,0.0005260861,0.001459749,0.002508782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005785041,0.002059761,0.08691667,0.00168741,0.0002369431,0.001394709,0.01918914,0.0002914892,0.0002534274,0.1630466,0.1049436,0.6194018],"study_design_scores_gemma":[0.0002267806,0.0006436511,0.1215099,0.01158478,0.0003139124,0.002630917,0.2261466,0.0007717757,0.0004301334,0.3905446,0.2448822,0.0003147947],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.122282,0.1051184,0.002396382,0.7073692,0.009250972,0.00006666025,0.0002748907,0.0000551543,0.05318643],"genre_scores_gemma":[0.8387237,0.08158637,0.001712766,0.04735503,0.005246717,0.0000986353,0.0001894187,0.00004546955,0.02504192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02273675,"threshold_uncertainty_score":0.07606202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02025321569372825,"score_gpt":0.3092430579913781,"score_spread":0.2889898422976498,"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."}}