{"id":"W1569274598","doi":"10.19173/irrodl.v15i6.1935","title":"An approach for externalization of expert tacit knowledge using a query management system in an e-learning environment","year":2014,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Externalization; Tacit knowledge; Explicit knowledge; Knowledge management; Subject (documents); Subject-matter expert; Expert system; World Wide Web; Artificial intelligence","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":[0.02306321,0.0001144968,0.0003235474,0.0002758601,0.0001452511,0.00006528574,0.0007348215,0.00005460927,0.00006083944],"category_scores_gemma":[0.0005599408,0.00009070864,0.00003798724,0.0003492835,0.0001195881,0.0001652778,0.0002510909,0.0005670461,0.000001710889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001776985,"about_ca_system_score_gemma":0.00002697605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004394745,"about_ca_topic_score_gemma":0.000002165785,"domain_scores_codex":[0.9926848,0.00582632,0.0005416934,0.0003410814,0.0003648982,0.0002412024],"domain_scores_gemma":[0.9986588,0.0005873914,0.0002792767,0.000253287,0.0001770841,0.0000441302],"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":[0.001465666,0.002284108,0.2346405,0.01275461,0.0003002208,0.00001500128,0.0125703,0.04164725,0.005336241,0.2579398,0.0001668544,0.4308795],"study_design_scores_gemma":[0.005973209,0.001601277,0.1048096,0.03545105,0.00006206917,0.00005545686,0.06077359,0.7041135,0.0003369306,0.001002086,0.0850909,0.0007302523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1754016,0.005960263,0.8039132,0.0001367596,0.0001184434,0.001939441,0.00001292415,0.00001891447,0.01249842],"genre_scores_gemma":[0.9866767,0.0006048207,0.01192328,0.00002093189,0.00006185572,0.0002859806,0.0002043154,0.00001893329,0.0002031978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8112751,"threshold_uncertainty_score":0.7993295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1793234869725969,"score_gpt":0.5220524801915015,"score_spread":0.3427289932189046,"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."}}