{"id":"W4323316307","doi":"10.26434/chemrxiv-2023-nvxkg","title":"Digital pipette: Open hardware for liquid transfer in self-driving laboratories","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pipette; Robot; Computer science; Context (archaeology); Transfer (computing); Simulation; Artificial intelligence; Chemistry","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0004962187,0.0004614315,0.0003667131,0.0004738046,0.0002925369,0.0007925731,0.00162633,0.000807009,0.005527],"category_scores_gemma":[0.001203233,0.0002949403,0.0003115901,0.0003442911,0.0008553458,0.001282567,0.001830223,0.0006788892,0.001685908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004227807,"about_ca_system_score_gemma":0.0004215727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003331892,"about_ca_topic_score_gemma":0.0003220571,"domain_scores_codex":[0.9991912,0.00006401974,0.00003859844,0.0001190086,0.0005195382,0.00006757455],"domain_scores_gemma":[0.9993408,0.0001181709,0.00009345292,0.0002195201,0.0001274416,0.000100553],"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":[0.0004780098,0.0002360183,0.001649754,0.000708597,0.00004785898,0.0003199346,0.0003307602,0.01292115,0.6307483,0.01779695,0.01059592,0.3241667],"study_design_scores_gemma":[0.0003174409,0.001995944,0.005680584,0.0001688218,0.00007784263,0.001132604,0.0001387993,0.1847805,0.6275584,0.01344532,0.1645485,0.0001552334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0961867,0.001228751,0.8742136,0.0004277445,0.0004973083,0.0003052842,0.0003830743,0.01553817,0.0112193],"genre_scores_gemma":[0.5349877,0.0005928529,0.4508894,0.0003620068,0.0001226292,0.000436051,0.000527329,0.0005368867,0.01154501],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9983737,"threshold_uncertainty_score":0.0184896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03389210887200624,"score_gpt":0.2648255232396229,"score_spread":0.2309334143676167,"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."}}