{"id":"W3008439937","doi":"10.1101/2020.02.27.961847","title":"Candidate stress biomarkers for queen failure diagnostics","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Insect and Pesticide Research","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Food and Agriculture; Genome British Columbia; Genome Canada; U.S. Department of Agriculture","keywords":"Stressor; Shock (circulatory); Heat shock protein; Biology; Heat stress; Genetics; Medicine; Neuroscience; Internal medicine; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005574363,0.0005119087,0.0004626949,0.0008808152,0.0002318267,0.0007130033,0.0003636534,0.0005732463,0.002197503],"category_scores_gemma":[0.0004626334,0.0001958007,0.0002315734,0.0003964739,0.0002831976,0.0003031213,0.0003313886,0.0005250286,0.0005645305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005029888,"about_ca_system_score_gemma":0.0002356475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005675328,"about_ca_topic_score_gemma":0.001057186,"domain_scores_codex":[0.9997457,0.00005258159,0.00002164928,0.00007341283,0.00007170771,0.00003486719],"domain_scores_gemma":[0.9993338,0.0001533137,0.0002496949,0.00004474175,0.0001331556,0.00008517596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007580043,0.00009054607,0.06773381,0.0004357446,0.00005763841,0.0001889674,0.00008556949,0.0005019146,0.9139003,0.0001551155,0.0008275701,0.01526486],"study_design_scores_gemma":[0.00005556218,0.00112745,0.5600823,0.000125335,0.0001519957,0.001041425,0.00042127,0.009612136,0.4189,0.0008355251,0.007591037,0.00005592757],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684992,0.010652,0.01526179,0.0005358937,0.0001334484,0.0001394057,0.002559232,0.0003767147,0.001842313],"genre_scores_gemma":[0.9754239,0.002066553,0.01792316,0.0002411112,0.00005725379,0.00008817826,0.001469098,0.00003529615,0.002695385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002197503,"threshold_uncertainty_score":0.007351398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02275642332340053,"score_gpt":0.2367708739067575,"score_spread":0.214014450583357,"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."}}