{"id":"W2009054217","doi":"10.1021/la900255u","title":"Small-Molecule Diffusion through Polycrystalline Triglyceride Networks Quantified Using Fluorescence Recovery after Photobleaching","year":2009,"lang":"en","type":"article","venue":"Langmuir","topic":"Food Chemistry and Fat Analysis","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Food and Agriculture","keywords":"Fluorescence recovery after photobleaching; Photobleaching; Crystallite; Fluorescence; Triglyceride; Diffusion; Chemistry; Molecule; Photochemistry; Analytical Chemistry (journal); Chromatography; Crystallography; Organic chemistry; Optics; Biochemistry; Physics; Thermodynamics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001762962,0.0002845095,0.0001819015,0.0001740934,0.0001146339,0.0002426605,0.0002864106,0.0002609947,0.0009218868],"category_scores_gemma":[0.0003575449,0.0001382677,0.0001256298,0.0001795454,0.0002366323,0.0005026174,0.0001285729,0.0004308938,0.0002355238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003315463,"about_ca_system_score_gemma":0.0001113117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008475407,"about_ca_topic_score_gemma":0.001070616,"domain_scores_codex":[0.9998962,0.00001187831,0.000004291066,0.0000367308,0.00003583042,0.00001499733],"domain_scores_gemma":[0.9997818,0.0001137206,0.0000410306,0.00002006738,0.00002847329,0.00001497832],"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":[0.00003103717,0.000008054593,0.0001000545,0.00001200597,0.000002080749,0.000014881,0.00001007207,0.0003389258,0.9986317,0.00005517886,0.00000754311,0.0007885967],"study_design_scores_gemma":[0.000004262638,0.0000357484,0.0005727253,0.000001379971,0.000003628566,0.00002169181,0.00000943228,0.006027656,0.9931459,0.00003092457,0.0001436439,0.000002954071],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9685587,0.0002093607,0.03021688,0.00003982066,0.000006193736,0.00001599801,0.0001645724,0.0001408415,0.0006475881],"genre_scores_gemma":[0.9770478,0.0003756105,0.02049622,0.00001041023,0.000002108564,0.00004140672,0.0002427111,0.00003658272,0.001747119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009218868,"threshold_uncertainty_score":0.003084004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02619236894773702,"score_gpt":0.2201505837211331,"score_spread":0.193958214773396,"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."}}