{"id":"W7062981739","doi":"","title":"Welfare, wool, women and where it began","year":2017,"lang":"en","type":"article","venue":"Figshare","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homecoming; Session (web analytics); Animal welfare; Welfare; Government (linguistics); Quarter (Canadian coin)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003363555,0.000751951,0.0007033588,0.0007653083,0.005994298,0.009457578,0.001250419,0.003163402,0.09148946],"category_scores_gemma":[0.004306669,0.0003174831,0.0003131704,0.0005833221,0.002032561,0.00406807,0.006454701,0.006945098,0.03322436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006051894,"about_ca_system_score_gemma":0.01322825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03705705,"about_ca_topic_score_gemma":0.09094994,"domain_scores_codex":[0.9966881,0.000347381,0.0000801043,0.0002608702,0.001749371,0.0008741814],"domain_scores_gemma":[0.9942077,0.00009098607,0.00009841318,0.00009120377,0.00132956,0.004182093],"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":[0.00001633602,0.00002573465,0.0002750693,0.00003306996,0.000001803272,0.00004864396,0.0004813528,0.00000602825,0.0002159789,0.002609021,0.9713197,0.0249672],"study_design_scores_gemma":[0.000002768358,0.00002703792,0.001169616,0.00004772543,9.340416e-7,0.00004262873,0.0009656477,0.000006634622,0.00002584193,0.0002389565,0.9974669,0.000005429951],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.006578553,0.01092352,0.0006467939,0.6042998,0.1045113,0.0003356721,0.001102754,0.0003686836,0.2712328],"genre_scores_gemma":[0.01526358,0.004735193,0.0003685459,0.02343866,0.003476585,0.0001163613,0.0005985722,0.0001934937,0.951809],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09148946,"threshold_uncertainty_score":0.3060628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02501241023602314,"score_gpt":0.2558673168786988,"score_spread":0.2308549066426757,"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."}}