{"id":"W3093569432","doi":"10.1145/3415177","title":"Leveraging Peer Support for Mature Immigrants Learning to Write in Informal Contexts","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Software deployment; Peer learning; Immigration; Peer feedback; Computer science; Peer support; Negotiation; Literacy; Leverage (statistics); Public relations; Psychology; Pedagogy; Sociology; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004564157,0.0007663198,0.000285238,0.001090349,0.002671499,0.003833926,0.001612713,0.001131471,0.006163978],"category_scores_gemma":[0.02524219,0.0002900439,0.0004059434,0.0003736374,0.0009712763,0.004206993,0.006870152,0.000992415,0.002297795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003804356,"about_ca_system_score_gemma":0.001733979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006767081,"about_ca_topic_score_gemma":0.001874069,"domain_scores_codex":[0.995806,0.002753578,0.0001595731,0.0003922,0.0005549798,0.0003336793],"domain_scores_gemma":[0.9853689,0.007450555,0.0009867628,0.001917489,0.001610649,0.002665663],"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":[0.0005200049,0.003020222,0.0444672,0.001363494,0.0001136051,0.004546832,0.1520394,0.001302922,0.03742139,0.005716068,0.01211433,0.7373745],"study_design_scores_gemma":[0.0008564596,0.01383503,0.08101113,0.002929733,0.0007235447,0.007984216,0.2591743,0.03751959,0.04306831,0.0467222,0.5054494,0.0007262394],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8435454,0.0004018651,0.09177462,0.0038413,0.0003276193,0.002069255,0.0001170914,0.003762052,0.05416076],"genre_scores_gemma":[0.924911,0.0002246262,0.06503896,0.0004102602,0.000149455,0.0008189026,0.0001085921,0.0002108249,0.008127348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006163978,"threshold_uncertainty_score":0.02413785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09162598735691602,"score_gpt":0.4053014968539309,"score_spread":0.3136755094970149,"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."}}