{"id":"W2006844559","doi":"10.1139/f00-151","title":"Prediction and the aquatic sciences","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Predictive modelling; Set (abstract data type); Computer science; Data science; SPARK (programming language); Probabilistic logic; Management science; Artificial intelligence; Machine learning; Engineering; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.006470202,0.0008979825,0.001075106,0.002273311,0.001456833,0.005847374,0.001400631,0.003647451,0.007044117],"category_scores_gemma":[0.0169353,0.0002807854,0.0006774795,0.001959849,0.01272831,0.008750118,0.003844572,0.00469283,0.0009587639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004045677,"about_ca_system_score_gemma":0.003301523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009450742,"about_ca_topic_score_gemma":0.00372676,"domain_scores_codex":[0.9959937,0.002090477,0.0001650068,0.0005528273,0.0009813674,0.0002165927],"domain_scores_gemma":[0.9886078,0.008534698,0.0006727912,0.0006727992,0.001091533,0.0004203841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002289412,0.00002652689,0.001469483,0.0002418614,0.00003726733,0.00008494345,0.000283824,0.009995545,0.00007710416,0.9229192,0.01221915,0.05262231],"study_design_scores_gemma":[0.000004837036,0.00001205491,0.0003872352,0.0001416245,0.000004937243,0.00003421022,0.0001273161,0.00424091,0.00003235406,0.9664825,0.02851915,0.00001288546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01934735,0.2159947,0.2201611,0.243285,0.005666084,0.0001495271,0.0008029509,0.0005248025,0.2940684],"genre_scores_gemma":[0.7401461,0.1469613,0.06233823,0.01553328,0.009157639,0.0003397484,0.000745541,0.0001717803,0.02460632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009450742,"threshold_uncertainty_score":0.03421813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315519489508299,"score_gpt":0.2112528196684848,"score_spread":0.1880976247734018,"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."}}