{"id":"W2887597315","doi":"10.5539/cis.v11n3p112","title":"A Semantic Recommender Engine for Idea Generation Improvement","year":2018,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Recommender system; Workflow; Key (lock); Ideation; Context (archaeology); Quality (philosophy); Focus (optics); Matching (statistics); Semantic Web; Knowledge management; Order (exchange); Semantic technology; Data science; World Wide Web; Semantic computing","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":[0.001032029,0.00004060286,0.00004247735,0.0001368758,0.0008423068,0.0004311972,0.0001484341,0.00001475459,0.00002097795],"category_scores_gemma":[0.00004234346,0.00003684782,0.00001207365,0.0002722514,0.0001912555,0.003413964,0.00008165422,0.0000179875,0.00002604764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003432439,"about_ca_system_score_gemma":0.00004533097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000019685,"about_ca_topic_score_gemma":0.00002704348,"domain_scores_codex":[0.9994388,0.000006755058,0.0001346677,0.00008611702,0.0001716515,0.0001620307],"domain_scores_gemma":[0.9995801,0.00001572716,0.00004521462,0.00006803558,0.0002384936,0.00005244173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002588295,0.00000735569,0.0001973989,0.00001634952,0.000003098588,1.902428e-8,0.01772228,0.00001599325,0.0001595608,0.0904526,0.007009252,0.8844135],"study_design_scores_gemma":[0.0003091059,0.0001319116,0.001748461,0.0000102016,0.000004325851,2.172389e-7,0.0006167502,0.6604814,0.0006531209,0.0007873424,0.3351304,0.0001267518],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04916273,0.000008659806,0.9131538,0.0009792538,0.001261783,0.0003870631,0.000001040593,0.00005731582,0.0349884],"genre_scores_gemma":[0.9906704,0.00001964222,0.007512675,0.001021647,0.0005975302,0.00001327854,0.000004357852,0.000001191075,0.00015924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9415077,"threshold_uncertainty_score":0.6478428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03984875128448905,"score_gpt":0.3135345158743553,"score_spread":0.2736857645898663,"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."}}