{"id":"W3034030848","doi":"","title":"Tim Kelsall Orbituary","year":2020,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001667047,0.0001029523,0.0001602942,0.00004541323,0.00009967572,0.00004443089,0.0002622529,0.00009814282,0.001048122],"category_scores_gemma":[0.006016287,0.0001027427,0.00003800811,0.0001904443,0.0001046849,0.00003629,0.00004050563,0.0002985068,0.0005212303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000151898,"about_ca_system_score_gemma":0.0007628203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002533731,"about_ca_topic_score_gemma":0.004690107,"domain_scores_codex":[0.9988902,0.00004115789,0.0001779091,0.0002017287,0.0002302425,0.0004587167],"domain_scores_gemma":[0.9978282,0.0005102163,0.00001872386,0.0002177503,0.0001003212,0.001324763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002381362,0.00004680917,0.0003200599,0.0004656591,0.00004348188,0.0005904211,0.0009053204,0.00006381185,0.00205926,0.5149506,0.4721456,0.008385204],"study_design_scores_gemma":[0.000618728,0.0003089543,0.004698677,0.00004785612,0.00008935019,0.00001855985,0.0003494903,0.06754062,0.0001163121,0.8783592,0.04718098,0.0006712501],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1599752,0.0003092953,0.548535,0.0562634,0.0006250649,0.001766519,0.002359212,0.000586084,0.2295802],"genre_scores_gemma":[0.9689682,0.00001092312,0.02655011,0.003463325,0.0001824105,0.000007423799,0.00001552419,0.00002810668,0.00077401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8089929,"threshold_uncertainty_score":0.9998651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1705772098287292,"score_gpt":0.3466852000977804,"score_spread":0.1761079902690512,"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."}}