{"id":"W7109556055","doi":"10.59350/z90e5-nkk09","title":"ScholCommLab Welcomes Visitors from ASIS&T","year":2018,"lang":"","type":"article","venue":"","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Globe; Information system; Work (physics); Government (linguistics)","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003534427,0.0005728109,0.0005677209,0.0002359322,0.0005557725,0.00372349,0.003476426,0.0003162368,0.01006228],"category_scores_gemma":[0.0001303597,0.0005423886,0.00026053,0.0007842329,0.0005973607,0.0056664,0.002539495,0.0003816467,0.07176743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001031675,"about_ca_system_score_gemma":0.000296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001379539,"about_ca_topic_score_gemma":0.0006912136,"domain_scores_codex":[0.9960457,0.0001165451,0.0008327947,0.001542933,0.0004873943,0.0009746165],"domain_scores_gemma":[0.9952684,0.0002573064,0.0002580262,0.003229791,0.0002669102,0.0007195797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004844266,0.0005281522,0.01360691,0.00002150385,0.0002580598,0.00001268502,0.001117944,0.000001834717,0.0002216586,0.06720209,0.3379884,0.5789923],"study_design_scores_gemma":[0.0006836978,0.000125538,0.01062114,0.0000694779,0.00002624065,0.00001193463,0.00004421805,0.002114082,0.001395122,0.008067756,0.976003,0.0008377867],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09629883,0.0007887582,0.4479524,0.003841658,0.009059217,0.000320001,0.0002646454,0.0004363364,0.4410382],"genre_scores_gemma":[0.9005156,0.00009201506,0.07091849,0.005138161,0.003253807,0.00001197636,0.0001230013,0.00004390847,0.01990307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8042167,"threshold_uncertainty_score":0.9997028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06189546745860297,"score_gpt":0.2862404930718068,"score_spread":0.2243450256132039,"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."}}