{"id":"W2912049494","doi":"10.1108/ils-01-2019-138","title":"Inaugural issue perspectives on<i>Information and Learning Sciences</i>as an integral scholarly nexus","year":2019,"lang":"en","type":"article","venue":"Information and Learning Sciences","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Scholarship; Sociology; Originality; Scholarly communication; Value (mathematics); Scope (computer science); Engineering ethics; Social science; Computer science; Political science; Engineering; Publishing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.002634371,0.0001826221,0.0001705169,0.0005920555,0.001744182,0.00473403,0.000589798,0.00008320696,0.00004070931],"category_scores_gemma":[0.0009643612,0.0001463761,0.00003475782,0.000948663,0.0004176329,0.02352205,0.0001671705,0.0009605614,0.0004363582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003373126,"about_ca_system_score_gemma":0.0001841629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002081973,"about_ca_topic_score_gemma":0.000002471603,"domain_scores_codex":[0.9981068,0.000236491,0.0003428027,0.0002946032,0.0006687347,0.0003505892],"domain_scores_gemma":[0.999022,0.0001806701,0.0002993545,0.000147044,0.0002018621,0.0001490499],"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":[0.00003053844,0.00005210362,0.0420036,0.00007256167,0.00001776778,0.000001599737,0.1555442,0.08349175,0.00009080674,0.334057,0.0001577696,0.3844803],"study_design_scores_gemma":[0.0004891758,0.002232048,0.01036959,0.00009061811,0.000005040506,0.00005521363,0.09861128,0.8339695,0.00003142751,0.00108671,0.05268023,0.0003791604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644417,0.0000962293,0.004356163,0.003823612,0.0002229077,0.0001378421,6.518687e-7,0.0002749056,0.02664598],"genre_scores_gemma":[0.9917779,0.00005811125,0.006413134,0.001003622,0.00004888447,0.000002511205,0.000006682792,0.00000299877,0.0006861589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7504777,"threshold_uncertainty_score":0.9995554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009488302127880023,"score_gpt":0.2757324218230698,"score_spread":0.2662441196951898,"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."}}