{"id":"W6904737977","doi":"10.1371/journal.pone.0259712.g004","title":"Study samples (marked as P1, P2, etc.), their nearest three neighbors, and a random selection of 25 Canadian and 25 global SARS-CoV-2 sequences for context.","year":2021,"lang":"en","type":"other","venue":"Figshare","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Feature selection; Sequence (biology); Random sequence; k-nearest neighbors algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007406326,0.0005573547,0.0004646586,0.001386268,0.0009272798,0.0004739065,0.0006933896,0.0005743007,0.1130565],"category_scores_gemma":[0.002904197,0.0003365525,0.0003593747,0.002040175,0.0004171807,0.000252106,0.0006316054,0.0003905851,0.02785899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006073053,"about_ca_system_score_gemma":0.002526565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06692213,"about_ca_topic_score_gemma":0.2725414,"domain_scores_codex":[0.9996501,0.0000443862,0.00002172593,0.0001132912,0.0001150906,0.00005544693],"domain_scores_gemma":[0.9988487,0.0001923842,0.00008076866,0.0002159061,0.0005050148,0.0001572875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002250402,0.0001646121,0.01848969,0.0008246585,0.00008753879,0.0004762678,0.0002188483,0.0009715759,0.03448342,0.001401015,0.7496758,0.1909561],"study_design_scores_gemma":[0.0005458155,0.0003985102,0.1116278,0.0002512824,0.0002241475,0.0007118104,0.0007075233,0.00257851,0.01625163,0.001268578,0.8653486,0.00008581476],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0920415,0.002135376,0.03678101,0.002294257,0.002084287,0.00510338,0.7286522,0.006668116,0.12424],"genre_scores_gemma":[0.1904077,0.001559627,0.09097692,0.00210959,0.0004129168,0.002862415,0.6010751,0.002844842,0.1077509],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9330779,"threshold_uncertainty_score":0.3782117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06204877688954163,"score_gpt":0.3202878245536225,"score_spread":0.2582390476640808,"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."}}