{"id":"W4321019709","doi":"10.1002/fsh.10884","title":"Synthesizing Professional Opinion and Published Science to Build a Conceptual Model of Walleye Recruitment","year":2023,"lang":"en","type":"article","venue":"Fisheries","topic":"Conservation, Ecology, Wildlife Education","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"U.S. Geological Survey; U.S. Fish and Wildlife Service; Wisconsin Department of Natural Resources; Great Lakes Fishery Commission","keywords":"Conceptual model; Data science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006108748,0.00008065574,0.0001050919,0.00007851203,0.0002254838,0.00004361776,0.0002176078,0.00004071891,0.0004768751],"category_scores_gemma":[0.0007282497,0.00007625162,0.00001374009,0.000613446,0.0006556376,0.0006608717,0.0003547913,0.00005508633,0.00004616768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001349297,"about_ca_system_score_gemma":0.0001276443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009321494,"about_ca_topic_score_gemma":0.0001028259,"domain_scores_codex":[0.9989414,0.00003295271,0.000195425,0.0003088494,0.0003033896,0.0002180294],"domain_scores_gemma":[0.9994928,0.000120422,0.00007452226,0.0001883827,0.00003000686,0.00009387037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003623051,0.00008594682,0.8751516,0.00002167438,0.000006480706,3.146638e-7,0.01408789,0.002234094,0.03094343,0.001371737,0.07153546,0.00452508],"study_design_scores_gemma":[0.0001154195,0.00005920963,0.9709768,0.00003281809,0.000002930642,0.000001009407,0.002210198,0.01052387,0.001302861,0.001099835,0.01354677,0.0001282267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984163,0.00000545105,0.0000775448,0.0136838,0.000482148,0.0004236088,0.000007577997,0.00005218777,0.001104671],"genre_scores_gemma":[0.9937907,0.00001072128,0.004105705,0.0004032878,0.00003026566,0.0002120779,0.000006874793,0.000008168598,0.001432126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0958252,"threshold_uncertainty_score":0.5221447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08899826491343327,"score_gpt":0.3155188223250996,"score_spread":0.2265205574116664,"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."}}