{"id":"W4417021401","doi":"10.1108/978-1-64113-325-820251014","title":"Preparing Preservice Teachers Through Service-Learning","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Service-Learning and Community Engagement","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Teacher education; Qualitative research; Field (mathematics); Multiculturalism; Immigration; Qualitative property; Multicultural education; Semi-structured interview; Component (thermodynamics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001573607,0.0004555335,0.0005007508,0.000111507,0.00150378,0.0003057622,0.001537009,0.0007084793,0.007459988],"category_scores_gemma":[0.0000861218,0.0004868122,0.0002134982,0.0001250718,0.00009444778,0.0003939862,0.0008033983,0.00247968,0.003913076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003222165,"about_ca_system_score_gemma":0.0004427764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02639142,"about_ca_topic_score_gemma":0.03149284,"domain_scores_codex":[0.9968835,0.0005233637,0.0004029726,0.0005762429,0.000984331,0.0006296109],"domain_scores_gemma":[0.9977118,0.0005217058,0.0003544879,0.0009614262,0.0002852913,0.0001652997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003530133,0.00006400517,0.000435289,0.0003713078,0.000536675,0.000007655227,0.2218951,0.001926563,0.000009337604,0.7428078,0.01588679,0.01602418],"study_design_scores_gemma":[0.0002184518,0.00004927859,0.00002860445,0.0003259546,0.00009990526,6.982232e-7,0.02357592,0.00009546347,0.00000332672,0.003689772,0.9713405,0.0005721635],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000438924,0.0004092607,0.00006054083,0.00184889,0.0004726435,0.0005873812,0.000002178713,0.000840629,0.9953396],"genre_scores_gemma":[0.008856882,0.0007035481,0.0006983813,0.002092858,0.0004546907,0.00001559333,0.00006826824,0.000126086,0.9869837],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9554537,"threshold_uncertainty_score":0.9998217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05219149390140589,"score_gpt":0.3080710396039836,"score_spread":0.2558795457025778,"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."}}