{"id":"W2807156594","doi":"10.1038/s41598-018-26433-1","title":"Correlative atomic force microscopy quantitative imaging-laser scanning confocal microscopy quantifies the impact of stressors on live cells in real-time","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; University of Regina","keywords":"Correlative; Confocal; Confocal microscopy; Atomic force microscopy; In situ; Biophysics; Confocal laser scanning microscopy; Microscopy; Nanotechnology; Live cell imaging; Cell; Chemistry; Materials science; Cell biology; Biology; Pathology; Biochemistry; Optics; Medicine; Physics","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":[0.002046362,0.0009348743,0.0009064685,0.001496894,0.0006966786,0.0008168618,0.001364905,0.001214786,0.003110997],"category_scores_gemma":[0.00157623,0.000487295,0.0004436583,0.0008206437,0.001245644,0.001005336,0.0006835929,0.00123464,0.0009696757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000925429,"about_ca_system_score_gemma":0.0007761994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001556519,"about_ca_topic_score_gemma":0.003102583,"domain_scores_codex":[0.998041,0.0002979085,0.0001134794,0.0005294813,0.0008277486,0.0001904149],"domain_scores_gemma":[0.9980762,0.0006987657,0.0003098204,0.0003618215,0.0004805646,0.00007287276],"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":[0.00004740018,0.00006175126,0.001073658,0.0001406263,0.00002166264,0.00004254907,0.00005068787,0.0003598388,0.9881216,0.0005997413,0.0003584378,0.009122094],"study_design_scores_gemma":[0.00001728447,0.0001705094,0.008066065,0.00001899719,0.00003609456,0.0002082652,0.00007011856,0.01337507,0.9731565,0.0006098665,0.004236679,0.00003460068],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3455406,0.003862493,0.6332187,0.0008348141,0.0002201132,0.0007681755,0.003072445,0.004422805,0.008059909],"genre_scores_gemma":[0.4717462,0.003628938,0.5148857,0.0005181591,0.0001317217,0.001706445,0.00126986,0.0003707904,0.005742195],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003110997,"threshold_uncertainty_score":0.0108223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01252548575417315,"score_gpt":0.3345055469375057,"score_spread":0.3219800611833326,"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."}}