{"id":"W2184941380","doi":"10.36510/learnland.v6i2.619","title":"Developing Interactive Andragogical Online Content for Nursing Students","year":2013,"lang":"en","type":"article","venue":"LEARNing Landscapes","topic":"E-Learning and COVID-19","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thematic analysis; Economic shortage; Andragogy; Online learning; Nurse education; Nursing; Medical education; Qualitative research; Nursing shortage; Content analysis; Psychology; Medicine; Pedagogy; Adult education; Computer science; Multimedia; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004206306,0.000120919,0.0001915464,0.00006952757,0.000816928,0.0002832486,0.000263237,0.00009810505,0.0002045778],"category_scores_gemma":[0.001442967,0.0001032524,0.00007927015,0.0001369899,0.0001025313,0.000222409,0.00004129235,0.0002979409,0.00008531213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001668858,"about_ca_system_score_gemma":0.000119898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001319134,"about_ca_topic_score_gemma":0.0004702739,"domain_scores_codex":[0.9985723,0.0002575325,0.0001863654,0.0002597969,0.0003320208,0.0003919451],"domain_scores_gemma":[0.9988424,0.0006564906,0.0001195244,0.00006816145,0.0001768318,0.0001366337],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002004953,0.0005649889,0.6501933,0.00006268178,0.0001881651,0.000009947657,0.1354756,0.0008412824,0.0004492154,0.01701172,0.004325733,0.1906769],"study_design_scores_gemma":[0.002740155,0.0005441906,0.2295069,0.0008868316,0.00007349425,0.000006467239,0.2906904,0.002630797,0.000112933,0.003387527,0.4685328,0.0008875098],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817041,0.0001369364,0.005776811,0.007803299,0.0003110027,0.0004044728,0.000001838672,0.0002347587,0.003626853],"genre_scores_gemma":[0.9906121,0.00004275604,0.002346314,0.0004768804,0.0003751167,0.0000551057,0.00002360567,0.0000162506,0.006051836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4642071,"threshold_uncertainty_score":0.6283233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07588410189653348,"score_gpt":0.3947607907958681,"score_spread":0.3188766888993346,"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."}}