{"id":"W2339148730","doi":"10.1139/cjfas-2015-0355","title":"Using temperature-dependent embryonic growth models to predict time of hatch of American lobster (<i>Homarus americanus</i>) in nature","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint John Regional Hospital; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Homarus; American lobster; Hatching; Biology; Fishing; Brood; Fishery; Larva; Ecology; Zoology; Animal science; Crustacean","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004852076,0.0004708834,0.0001844353,0.0004047054,0.0001987934,0.0004174172,0.0003095537,0.0002740698,0.0005439037],"category_scores_gemma":[0.001108721,0.0002401725,0.0003750026,0.000153879,0.0001417187,0.0002616759,0.0002356725,0.0002722408,0.0001873701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008878616,"about_ca_system_score_gemma":0.0007153824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04367992,"about_ca_topic_score_gemma":0.04836594,"domain_scores_codex":[0.9999175,0.00001891384,0.000005125743,0.0000361315,0.000009473127,0.000012853],"domain_scores_gemma":[0.9995277,0.0002674565,0.0000983217,0.00001644604,0.00006480855,0.00002527862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001579317,0.00006721097,0.1730945,0.00002181371,0.0001048379,0.00004449649,0.00004060728,0.8057307,0.004045119,0.0002185039,0.0003368349,0.01613743],"study_design_scores_gemma":[0.000006691052,0.00003606752,0.03455668,0.000005688791,0.00002292191,0.00001591992,0.00001706796,0.9641813,0.0009245133,0.000115308,0.0001097292,0.000008038992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841211,0.0001209148,0.01465956,0.00004874661,0.000007661867,0.00000869277,0.0002759677,0.0001167186,0.0006406316],"genre_scores_gemma":[0.9957862,0.00004737055,0.003275617,0.000008763356,0.000002565421,0.00001137587,0.0003707169,0.00001147882,0.0004858084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9563201,"threshold_uncertainty_score":0.08685136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01696921399335706,"score_gpt":0.2327870989776109,"score_spread":0.2158178849842538,"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."}}