{"id":"W2896679767","doi":"10.2116/analsci.18p013","title":"One Hour In Vivo-like Phenotypic Screening System for Anti-cancer Drugs Using a High Precision Surface Plasmon Resonance Device","year":2018,"lang":"en","type":"article","venue":"Analytical Sciences","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canarie","funders":"Japan Science and Technology Agency","keywords":"In vivo; Surface plasmon resonance; Chemistry; Cancer cell; Cell culture; Cancer; Drug; Ex vivo; Phenotypic screening; Phenotype; In vitro; Biophysics; Cancer research; Nanotechnology; Pharmacology; Gene; Biochemistry; Biology; Genetics; Materials science; Nanoparticle","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":[0.0002588883,0.000440856,0.000516971,0.0001859165,0.0002276301,0.000354637,0.0005901443,0.0006322854,0.001243007],"category_scores_gemma":[0.0001617901,0.0002553814,0.0003551001,0.0001423477,0.0001492286,0.0003085459,0.0003122155,0.0006718257,0.0008373496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447197,"about_ca_system_score_gemma":0.0002669626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002937,"about_ca_topic_score_gemma":0.000613094,"domain_scores_codex":[0.9996624,0.00004038577,0.0000218935,0.0001203273,0.0001131628,0.00004180977],"domain_scores_gemma":[0.9998176,0.00002788716,0.00003111678,0.00004495506,0.00004024135,0.00003828394],"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":[0.0000340214,0.00003255372,0.00005788476,0.00001443034,0.000002394283,0.0000159498,0.000006246471,0.0000288093,0.9987476,0.00002644903,0.00009678244,0.0009368331],"study_design_scores_gemma":[0.0000101367,0.0003772638,0.001283827,0.000001287189,0.00001276605,0.00008038759,0.00001199754,0.001242155,0.9953751,0.00003779058,0.001555367,0.00001193299],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8788949,0.0007642224,0.1111257,0.0005462907,0.0003638789,0.0004735437,0.001877247,0.00266808,0.003286158],"genre_scores_gemma":[0.8850287,0.0006658926,0.09463908,0.000749688,0.0001028517,0.0007853292,0.002184862,0.000196363,0.01564729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001243007,"threshold_uncertainty_score":0.004158258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0435329200849401,"score_gpt":0.3460594499268032,"score_spread":0.3025265298418631,"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."}}