{"id":"W4298535917","doi":"","title":"DNA, Content and genome size of some perennial Cicer spiecies. \"Cicer taxonomy: a flow cytometry approach\"","year":2010,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Genome size; Flow cytometry; Taxonomy (biology); DNA; Perennial plant; Genome; Content (measure theory); Biology; Computer science; Computational biology; Botany; Genetics; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000165565,0.0001358308,0.0002363804,0.001183206,0.0004828721,0.0003528431,0.0002425892,0.0003545881,0.001803982],"category_scores_gemma":[0.000384531,0.0001212191,0.000125864,0.0007164044,0.0002946468,0.0002759663,0.0001626916,0.0003000065,0.00033621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003415556,"about_ca_system_score_gemma":0.000181295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007661052,"about_ca_topic_score_gemma":0.006467643,"domain_scores_codex":[0.999911,0.000004801838,0.000005679052,0.00005173043,0.00001537835,0.00001137094],"domain_scores_gemma":[0.9996388,0.0001464777,0.00006290912,0.0000264589,0.00007543697,0.00004994207],"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":[0.000246416,0.00001822294,0.02390928,0.00005618873,0.00001346526,0.0000528672,0.0005790844,0.0001560753,0.9674706,0.0001550276,0.0001031426,0.00723944],"study_design_scores_gemma":[0.000009984476,0.0001658101,0.9622839,0.000007276508,0.00003168122,0.000275895,0.0003564519,0.0004912345,0.03344091,0.0001063275,0.002821729,0.000008867657],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973953,0.000290112,0.0002849814,0.00002313953,0.000003848454,0.000006860937,0.001225957,0.000008433136,0.0007613776],"genre_scores_gemma":[0.9916535,0.0002660761,0.001254032,0.00005848093,0.00001235373,0.00003838523,0.003223287,0.000009975516,0.003483762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007661052,"threshold_uncertainty_score":0.01523292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02987957612972925,"score_gpt":0.1892380594314854,"score_spread":0.1593584833017561,"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."}}