The ALMA assembly, integration, and verification project: a retrospective analysis
Bibliographic record
Abstract
The Atacama Large Millimeter/submillimeter Array (ALMA) is a joint project between astronomical organizations in Europe, North America, and East Asia, in collaboration with the Republic of Chile. ALMA consists of 54 twelve-meter antennas and 12 seven-meter antennas operating as an aperture synthesis array in the (sub)millimeter wavelength range. Assembly, Integration, and Verification (AIV) of the antennas was completed at the end of the year 2013, while the final optimization and complete expansion to validate all planned observing modes will continue. This paper compares the actually obtained results of the period 2008-2013 with the baselines that had been laid out in the early project-planning phase (2005-2007). First plans made for ALMA AIV had already established a two-phased project life-cycle: phase 1 for setting up necessary infrastructure and common facilities, and taking the first three antennas to the start of commissioning; and phase 2 focused on the steady state processing of the remaining units. Throughout the execution of the project this lifecycle was refined and two additional phases were added, namely a transition phase between phases 1 and 2, and a closing phase to address the project ramp-down. A sub-project called Accelerated Commissioning and Science Verification (ACSV) was carried out during the year 2009 in order to provide focus to the whole ALMA organization, and to accomplish the start-of-commissioning milestone. Early phases of CSV focused on validating the basic performance and calibration. Over time additional observing modes have been validated as capabilities expanded both in hardware and software. This retrospective analysis describes the originally presented project staffing plans and schedules, the underlying assumptions, identified risks and operational models, among others. For comparison actual data on staffing levels, the resultant schedule, additional risks identified and those that actually materialized, are presented. The observed similarities and differences are then analyzed and explained, and corresponding lessons learned are presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".