{"id":"W4236302849","doi":"10.1515/iupac.83.0329","title":"Artefact","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Computer science; Field (mathematics); Multidisciplinary approach; Process (computing); Data science; Management science; Sociology; Engineering; Linguistics; Biology; Social science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004599604,0.003026837,0.001550651,0.008285261,0.001993777,0.006970839,0.003830403,0.002639671,0.101567],"category_scores_gemma":[0.02807597,0.001364726,0.003322676,0.01055828,0.001315215,0.005204714,0.005863618,0.003408682,0.1397026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002572047,"about_ca_system_score_gemma":0.004373223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02104794,"about_ca_topic_score_gemma":0.03554612,"domain_scores_codex":[0.9929146,0.001605401,0.001511246,0.001661491,0.001756643,0.0005505824],"domain_scores_gemma":[0.9800623,0.006569192,0.00114612,0.008744647,0.002968871,0.0005088514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001158165,0.00002127324,0.001565562,0.0009890605,0.00005338243,0.00006655657,0.0001141985,0.000471544,0.0001401146,0.003762485,0.9838611,0.008839001],"study_design_scores_gemma":[0.00005527384,0.00000874034,0.00146536,0.0003417481,0.00001963864,0.0001036465,0.00009903398,0.0002775583,0.0002408621,0.003650084,0.9937071,0.00003091924],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000306223,0.0001447116,0.001470773,0.0001916314,0.000129376,0.00007112652,0.9905303,0.003383117,0.003772695],"genre_scores_gemma":[0.0007192724,0.0001149485,0.001769307,0.0001452897,0.00001591455,0.0001957916,0.995002,0.0006604801,0.001376934],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.101567,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758491133715803,"score_gpt":0.4269380046441678,"score_spread":0.4093530933070098,"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."}}