{"id":"W4304890618","doi":"10.1242/jeb.245136","title":"Swordfish and opahs tweak haemoglobin to suit warmer lifestyles","year":2022,"lang":"en","type":"article","venue":"Journal of Experimental Biology","topic":"Physiological and biochemical adaptations","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Swordfish; Fish <Actinopterygii>; Fishery; Yellowfin tuna; Tuna; Biology; Zoology","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":[0.0007144664,0.0003354657,0.0002842016,0.0005499969,0.001079337,0.0009252902,0.0004386864,0.001020059,0.004629529],"category_scores_gemma":[0.001316103,0.0004112776,0.0004285511,0.0003934885,0.002441585,0.001388465,0.001817692,0.001442282,0.001399874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041049,"about_ca_system_score_gemma":0.0007280733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02014077,"about_ca_topic_score_gemma":0.04844524,"domain_scores_codex":[0.9995759,0.00003045314,0.00002574144,0.0001446797,0.0001483752,0.00007487004],"domain_scores_gemma":[0.9994345,0.00006526693,0.00008251127,0.00006825782,0.0002270163,0.0001224089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008763467,0.0001107333,0.2301785,0.001166483,0.0002084056,0.002031628,0.01216123,0.0005358297,0.3923927,0.01101703,0.05432945,0.2949916],"study_design_scores_gemma":[0.00009781598,0.0007053003,0.6559907,0.0004537494,0.0001124569,0.002596834,0.01158423,0.0003614268,0.02480359,0.003371238,0.2997447,0.0001778802],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9202664,0.003934158,0.006004668,0.01669967,0.00199155,0.0001508723,0.0009105611,0.0003957482,0.04964636],"genre_scores_gemma":[0.8570709,0.003685618,0.01951166,0.02071644,0.000544587,0.0001483847,0.00112047,0.0002268344,0.09697516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02014077,"threshold_uncertainty_score":0.04004705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786483730621992,"score_gpt":0.2693831063037522,"score_spread":0.2515182689975323,"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."}}