{"id":"W7024153605","doi":"","title":"Report of the 2018 North Sea Norway Pout (Trisopterus esmarkii) age reading exchange","year":2018,"lang":"en","type":"article","venue":"Figshare","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Otolith; Norwegian; North sea; Danish; Age structure; Quarter (Canadian coin); Fish <Actinopterygii>","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":[0.0016527,0.0004089391,0.0002235169,0.001035821,0.001725872,0.001027515,0.0006037704,0.0007424024,0.00646742],"category_scores_gemma":[0.003705112,0.0002223097,0.000266469,0.0005543071,0.0003919687,0.0007507016,0.00138087,0.00099606,0.002092183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476865,"about_ca_system_score_gemma":0.00173147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03703442,"about_ca_topic_score_gemma":0.04711657,"domain_scores_codex":[0.9985203,0.0001050569,0.0001233398,0.0002676394,0.000789766,0.0001938567],"domain_scores_gemma":[0.9969816,0.0004111954,0.000669395,0.000192805,0.001360583,0.0003844987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007925034,0.0006510443,0.7423304,0.0003163585,0.00007153006,0.01522646,0.01500871,0.0003880629,0.01025738,0.002005751,0.05225192,0.1606999],"study_design_scores_gemma":[0.00001482746,0.001130697,0.7324963,0.0002989632,0.00006235674,0.006203727,0.01212519,0.0007335115,0.007274102,0.0004155695,0.239188,0.00005672823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9447796,0.0008170542,0.002758688,0.001939381,0.001403297,0.0004393077,0.005771901,0.0002132881,0.04187757],"genre_scores_gemma":[0.882621,0.001225523,0.004811557,0.002088853,0.000425055,0.0004944281,0.01412606,0.0001353935,0.0940721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03703442,"threshold_uncertainty_score":0.07363772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03969901470614832,"score_gpt":0.261760770173223,"score_spread":0.2220617554670747,"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."}}