{"id":"W2883553124","doi":"10.1186/s13071-018-3005-3","title":"Identification and preliminary characterization of Hc-clec-160, a novel C-type lectin domain-containing gene of the strongylid nematode Haemonchus contortus","year":2018,"lang":"en","type":"article","venue":"Parasites & Vectors","topic":"Helminth infection and control","field":"Veterinary","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; Chinese Academy of Sciences; State Key Laboratory of Veterinary Etiological Biology; Institute of Genetics; National Natural Science Foundation of China","keywords":"Haemonchus contortus; Biology; Caenorhabditis elegans; Gene knockdown; RNA interference; Nematode; Gene; Exon; C-type lectin; Molecular biology; Parasitology; Genetics; RNA; Lectin; Zoology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00009868722,0.0002872821,0.0002556778,0.0002949518,0.0001740444,0.0002013197,0.000178617,0.0003523526,0.0008998103],"category_scores_gemma":[0.0001910899,0.0001040288,0.0002876782,0.0001905902,0.0002420675,0.0001816099,0.0001765291,0.0003512256,0.0006200904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002006097,"about_ca_system_score_gemma":0.0002685645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005078616,"about_ca_topic_score_gemma":0.0007040902,"domain_scores_codex":[0.9999434,0.000003785825,0.000005338095,0.00002126839,0.00001793853,0.000008377677],"domain_scores_gemma":[0.9998412,0.00002699999,0.00003590332,0.00001599283,0.00002794298,0.00005194602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00002352325,0.00001169764,0.0003080666,0.00003503961,0.000002016342,0.0001384364,0.00001649746,0.00002778407,0.9986354,0.00004774371,0.00002524266,0.0007285607],"study_design_scores_gemma":[0.00005514648,0.0006406901,0.0742017,0.00004879873,0.00009331632,0.004570545,0.0002078777,0.003038104,0.8926668,0.0003195159,0.02412087,0.00003653783],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889413,0.0012026,0.005657602,0.0001517974,0.00004683364,0.0001031456,0.002434044,0.00004056179,0.001422124],"genre_scores_gemma":[0.955207,0.001593133,0.01751515,0.0002555179,0.00004403522,0.0001178884,0.01715269,0.00006157811,0.00805294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008998103,"threshold_uncertainty_score":0.003010213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920800179846479,"score_gpt":0.3021603844375124,"score_spread":0.2729523826390476,"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."}}