{"id":"W2553407139","doi":"10.1016/j.cryobiol.2016.09.086","title":"Generation and characterization of ice-binding protein knockdown in a model crop","year":2016,"lang":"en","type":"article","venue":"Cryobiology","topic":"Magnetic and Electromagnetic Effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Gene knockdown; Characterization (materials science); Crop; Computational biology; Chemistry; Environmental science; Nanotechnology; Biology; Agronomy; Materials science; Biochemistry; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001079084,0.00007957018,0.0001082472,0.00004405285,0.0000182905,0.000003122048,0.00005074129,0.0001363008,0.00002068316],"category_scores_gemma":[0.00005768955,0.00005876329,0.00001619042,0.00003729625,0.0000755992,0.000002799193,0.00003884786,0.00002607124,0.000002162004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006039572,"about_ca_system_score_gemma":0.00003236668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005291738,"about_ca_topic_score_gemma":0.00002060628,"domain_scores_codex":[0.9994128,0.00006020401,0.0001471557,0.0002075142,0.00002441523,0.0001479462],"domain_scores_gemma":[0.9997647,0.000007165511,0.0000589886,0.0001164593,0.00002781709,0.00002484641],"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":[0.00004023193,0.00001760833,0.0009981088,0.00001225116,0.000004029688,3.828391e-7,0.00001613594,0.000003499607,0.9917268,0.0002956056,0.00002563652,0.006859693],"study_design_scores_gemma":[0.0006265898,0.0006387676,0.002559042,0.00001858034,0.000004578721,0.000005961578,0.000001776678,0.001158024,0.9943669,0.00009102912,0.0004276375,0.0001011051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945042,0.00009168611,0.004795804,0.0001693036,0.00002800058,0.0002067606,0.00001084647,0.000003897085,0.0001895283],"genre_scores_gemma":[0.9980515,0.00009203833,0.0003603571,0.00003812258,0.00005959371,0.00003917502,0.0000704562,0.000007542325,0.001281252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006758588,"threshold_uncertainty_score":0.2396297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01034967822637142,"score_gpt":0.2256161838449952,"score_spread":0.2152665056186238,"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."}}