{"id":"W2355703607","doi":"","title":"Measures and Their Inspirations of Accelerating Lifelong Learning in Canada","year":2005,"lang":"en","type":"article","venue":"Kaifang jiaoyu yanjiu","topic":"Education Systems and Policy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lifelong learning; Government (linguistics); Learning society; Investment (military); Experiential learning; Adult Learning; Adult education; Business; Political science; Pedagogy; Knowledge management; Sociology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000472178,0.00005886128,0.0001161649,0.00006385384,0.0002490957,0.00003654579,0.00008304096,0.00003550383,0.00005064408],"category_scores_gemma":[0.0002665026,0.0000541919,0.00001521725,0.0002177369,0.00004188778,0.0001533022,0.00001396102,0.0001049455,0.000002628264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001772658,"about_ca_system_score_gemma":0.001377449,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9427798,"about_ca_topic_score_gemma":0.9927787,"domain_scores_codex":[0.9992236,0.0001549831,0.0002114684,0.0000965654,0.0001469905,0.000166354],"domain_scores_gemma":[0.9995631,0.0001444789,0.00009389465,0.0000671597,0.00006182458,0.00006952429],"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":[0.000001878155,0.00002292764,0.745423,0.00001849731,0.00001237076,4.917804e-7,0.1644854,0.0006697304,0.0006692761,0.01490555,0.001238697,0.07255224],"study_design_scores_gemma":[0.0003763473,0.00002188137,0.2926213,0.0001374109,0.000006252822,0.000001802354,0.1590891,0.0005272852,0.001079708,0.0002004899,0.5456193,0.0003190685],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693409,0.0004050068,0.00001556895,0.003333189,0.00009964694,0.00009900738,0.000002657915,0.00001603932,0.02668802],"genre_scores_gemma":[0.9986075,0.00003803414,0.0001242346,0.0002706774,0.0003684455,0.000008194781,0.000001452959,0.000005667199,0.0005757983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5443806,"threshold_uncertainty_score":0.2443534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05569175579724173,"score_gpt":0.3124157368768466,"score_spread":0.2567239810796049,"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."}}