{"id":"W3127374156","doi":"","title":"Principals’ Work in Ontario, Canada: Changing Demographics, Advancements in Information Communication Technology and Health and Wellbeing","year":2016,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demographics; Work (physics); Public relations; Information and Communications Technology; Geography; Sociology; Political science; Engineering; Computer science; World Wide Web; Demography","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":[0.002067611,0.0002688445,0.0004231819,0.001605345,0.01954707,0.004828982,0.001163276,0.000770255,0.003547351],"category_scores_gemma":[0.003246858,0.0006552262,0.0003211596,0.004259052,0.006583198,0.001445046,0.003487394,0.001601151,0.0005889836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06846578,"about_ca_system_score_gemma":0.1418371,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891139,"about_ca_topic_score_gemma":0.9967153,"domain_scores_codex":[0.9972585,0.0004183073,0.00008548211,0.0002468959,0.0008235507,0.001167308],"domain_scores_gemma":[0.9942978,0.0004508871,0.0006284109,0.0001201953,0.001604854,0.002897832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001549857,0.000140311,0.2504671,0.0003243211,0.00001997822,0.001409494,0.6881379,0.0001487143,0.001535393,0.002961633,0.01204318,0.04265701],"study_design_scores_gemma":[0.00001114166,0.00008688858,0.2236831,0.0001522203,0.00001003416,0.0001413891,0.7244273,0.00009446465,0.000135507,0.0001764726,0.05104047,0.00004097247],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798955,0.001424129,0.00031209,0.006969613,0.0000778114,0.0001187679,0.0005772493,0.00003358773,0.01059131],"genre_scores_gemma":[0.9838293,0.002166284,0.000409533,0.0007799094,0.00002021725,0.00005199438,0.0001972798,0.00002296116,0.01252254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06846578,"threshold_uncertainty_score":0.4967563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0549225308537826,"score_gpt":0.3151830389776874,"score_spread":0.2602605081239048,"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."}}