{"id":"W2296602696","doi":"10.1016/j.aquatox.2016.02.024","title":"Can ecological history influence response to pollutants? Transcriptomic analysis of Manila clam collected in different Venice lagoon areas and exposed to heavy metal","year":2016,"lang":"en","type":"article","venue":"Aquatic Toxicology","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Pollutant; Transcriptome; Pollution; Ecology; Ecosystem; Contamination; Environmental science; Biology; Ecotoxicology; Xenobiotic; Environmental chemistry; Gene expression; Gene; Chemistry; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001355576,0.0002577175,0.0003343277,0.0009216066,0.0005146149,0.0005166797,0.0001682405,0.0002938258,0.0009125076],"category_scores_gemma":[0.0001870568,0.0001699648,0.0002249086,0.0005793344,0.0003155765,0.0001845546,0.0003914344,0.0002055887,0.0001395799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003969773,"about_ca_system_score_gemma":0.0003937345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01339494,"about_ca_topic_score_gemma":0.04821825,"domain_scores_codex":[0.9998881,0.0000090642,0.000006087268,0.00004080655,0.00001736612,0.00003860536],"domain_scores_gemma":[0.9998918,0.00001626547,0.00002773894,0.000005808533,0.00003356373,0.0000247256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000543316,0.00004044869,0.2152138,0.00008901111,0.00008216613,0.0003043276,0.0009179674,0.000150443,0.7781894,0.00005994863,0.00007839292,0.004330749],"study_design_scores_gemma":[0.000002952804,0.0001206058,0.9898424,0.00001002113,0.00003257007,0.000137051,0.001131984,0.0001597255,0.007929885,0.00003106779,0.0005951237,0.000006843929],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998956,0.0002211281,0.0000966944,0.00002010557,0.000003905933,0.000004960708,0.0004303461,0.000001783586,0.0002650664],"genre_scores_gemma":[0.9970028,0.0002070395,0.0002615583,0.00006407287,0.000004672685,0.00001726955,0.0009297017,0.000004043193,0.001508925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01339494,"threshold_uncertainty_score":0.02663398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01367430964582204,"score_gpt":0.2225513246513397,"score_spread":0.2088770150055176,"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."}}