{"id":"W6948518240","doi":"10.5064/f6wblx4i/jhhg2q","title":"Aguessivognon_Coding_Definitions_Excerpts.pdf","year":2023,"lang":"ca","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Process (computing); Identification (biology); Product (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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005382683,0.001685312,0.001010482,0.008458127,0.002023154,0.003437009,0.002739707,0.001440031,0.3643478],"category_scores_gemma":[0.03469945,0.001253983,0.001103675,0.01647924,0.0008247335,0.002005314,0.00348859,0.002030958,0.1843008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004230792,"about_ca_system_score_gemma":0.008976309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04454292,"about_ca_topic_score_gemma":0.08946637,"domain_scores_codex":[0.9963013,0.001001681,0.0007731955,0.0005784534,0.0009384511,0.000406892],"domain_scores_gemma":[0.9724581,0.01229828,0.001392253,0.004547936,0.00852277,0.0007806854],"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":[0.00002411048,0.00001066713,0.0002413824,0.0005222701,0.000004740293,0.000006055109,0.000115408,0.00003874248,0.00004122629,0.0007172372,0.9948086,0.003469666],"study_design_scores_gemma":[0.0001306523,0.000008164006,0.002923905,0.0007042524,0.00001133397,0.0000198429,0.0005204986,0.00009072346,0.0002167647,0.00167448,0.9936715,0.00002777826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007692416,0.00001882208,0.0001898327,0.0000813762,0.00002532341,0.0001183472,0.9962715,0.0002019098,0.003016071],"genre_scores_gemma":[0.0007011846,0.00008558139,0.001727108,0.0001121214,0.00001345368,0.00341281,0.9883595,0.00036731,0.005220929],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3643478,"threshold_uncertainty_score":0.9066806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1681534399648958,"score_gpt":0.3801808754258962,"score_spread":0.2120274354610003,"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."}}