{"id":"W6894155735","doi":"10.5281/zenodo.826441","title":"Presentation Of The Paper \"A Metamodel Proposal For Developing Learning Ecosystems\" In Hcii 2017","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"E-Learning and Knowledge Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metamodeling; Presentation (obstetrics); Process (computing); Domain (mathematical analysis); Learning object; Experiential learning; Active learning (machine learning); Object (grammar)","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":[0.006993602,0.001511822,0.0007053897,0.002390835,0.001406749,0.006117659,0.003130611,0.004032622,0.03176526],"category_scores_gemma":[0.01032453,0.0007007244,0.002481067,0.00164541,0.001341109,0.00547188,0.003757259,0.005034862,0.01052591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002669152,"about_ca_system_score_gemma":0.004762122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003582222,"about_ca_topic_score_gemma":0.002374982,"domain_scores_codex":[0.9965841,0.00115535,0.000304884,0.0004774107,0.00123968,0.0002386056],"domain_scores_gemma":[0.9962481,0.0009784324,0.0001482535,0.0005154471,0.001640203,0.0004695767],"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":[0.0002679529,0.0003858776,0.0008069706,0.001902732,0.0001382231,0.001025319,0.003775419,0.01388907,0.01880511,0.3657584,0.307824,0.2854208],"study_design_scores_gemma":[0.00004259536,0.00008240216,0.0001508289,0.0005914624,0.00003762822,0.0003651161,0.0003191428,0.01180287,0.003680999,0.02645059,0.9564091,0.00006727227],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.002477671,0.001327744,0.9428214,0.01101015,0.009774714,0.00101471,0.0008964894,0.004713936,0.0259633],"genre_scores_gemma":[0.03761159,0.006031733,0.7873259,0.008750902,0.004419118,0.00302924,0.01328241,0.005448458,0.1341006],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03176526,"threshold_uncertainty_score":0.1062654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05199814981105561,"score_gpt":0.2775068697115174,"score_spread":0.2255087199004618,"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."}}