{"id":"W3418637","doi":"","title":"Previsione della fauna ittica mediante reti neurali artificiali.","year":2004,"lang":"it","type":"article","venue":"The Journal of Rheumatology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Fish <Actinopterygii>; Computer science; Consistency (knowledge bases); Abundance (ecology); Ecological network; Ecology; Artificial intelligence; Geography; Fishery; Ecosystem; Biology","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":[0.001898984,0.000604463,0.0004547451,0.001616613,0.0002287308,0.002561216,0.0009419736,0.001111715,0.007374623],"category_scores_gemma":[0.004621433,0.0002925146,0.0005344361,0.001302001,0.0008623535,0.002206668,0.0007547814,0.001317324,0.00232029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009454979,"about_ca_system_score_gemma":0.0004368565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003132624,"about_ca_topic_score_gemma":0.003657057,"domain_scores_codex":[0.999316,0.0002555283,0.00004235867,0.0001606513,0.0001944248,0.00003107005],"domain_scores_gemma":[0.9987881,0.000738212,0.00008701503,0.0001584438,0.0002015222,0.00002674173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001213359,0.00004613314,0.003394143,0.001078264,0.000132013,0.0001570144,0.0002559175,0.07283977,0.003721423,0.0724113,0.01255587,0.8332868],"study_design_scores_gemma":[0.00005475117,0.0002274393,0.01270407,0.0011828,0.000148438,0.0005728155,0.0002860031,0.553774,0.006809019,0.1927832,0.2313541,0.0001033656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02936596,0.09245043,0.7986659,0.005366946,0.001828371,0.0001540856,0.001283274,0.002523003,0.06836201],"genre_scores_gemma":[0.3728801,0.05662865,0.5061625,0.00129406,0.002245868,0.0005540389,0.002359156,0.000666523,0.05720909],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007374623,"threshold_uncertainty_score":0.02467054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500546984923834,"score_gpt":0.2404353435704197,"score_spread":0.2254298737211814,"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."}}