{"id":"W2972711812","doi":"10.1016/j.jare.2019.09.002","title":"Benefits of non-invasive methods compared to telemetry for distress analysis in a murine model of pancreatic cancer","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Research","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; European Social Fund; Deutsche Forschungsgemeinschaft; Federation of Canadian Municipalities","keywords":"Distress; Telemetry; Medicine; Receiver operating characteristic; Psychological intervention; Intensive care medicine; Internal medicine; Computer science; Psychiatry; Clinical psychology; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001669714,0.0001124365,0.000761792,0.0009654244,0.00003152426,0.000008993823,0.0003891203,0.00003649953,0.00002913839],"category_scores_gemma":[0.001155247,0.00008950471,0.0002101443,0.001205335,0.00006281006,0.0001347592,0.0001242379,0.0003036189,8.437223e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136846,"about_ca_system_score_gemma":0.0001371904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002271838,"about_ca_topic_score_gemma":0.00009268681,"domain_scores_codex":[0.9980612,0.000218769,0.0006943665,0.0001937364,0.0005283692,0.0003034943],"domain_scores_gemma":[0.9961364,0.001919854,0.0004520168,0.0002211745,0.001160054,0.0001105023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003620996,0.000229212,0.05070896,0.0004066679,0.0004719888,0.000006202727,0.0009394696,0.5156572,0.4167782,0.00004646511,0.00002283936,0.01111178],"study_design_scores_gemma":[0.006441805,0.01011014,0.3476405,0.004115555,0.0004440088,0.00002282727,0.006602341,0.3534923,0.2683719,0.002219526,0.00004116312,0.0004979435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98558,0.0005170271,0.0131591,0.00006137371,0.00003505801,0.0003260876,0.0001204139,0.000002519714,0.0001984523],"genre_scores_gemma":[0.8602643,0.0001470216,0.1393422,0.000004945186,0.00003856158,0.00001861237,0.00000194265,0.00001445011,0.0001679412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2969315,"threshold_uncertainty_score":0.3649896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3120245062676993,"score_gpt":0.5617218078444624,"score_spread":0.2496973015767631,"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."}}